Publications ordered by Type

The majority of the publications can also be obtained using Google Scholar where incomplete lists of citations are also given, similar as shown on the right. The publication list sorted by year can be found using this link.

Journal Papers

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    Look, A.; Rakitsch, B.; Kandemir, M.; Peters, J. (submitted). Sampling-Free Probabilistic Deep State-Space Models, Submitted to Transactions on Pattern Analysis and Machine Intelligence (PAMI).
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    Watson, J.; Song, C.; Weeger, O.; Gruner, T.; Le, A.T.; Hansel, K.; Headway, A.; Arenz, O.; Trojak, W.; Cranmer, M.; D’Eramo, C.; Bülow, F.; Goyal, T.; Peters, J.; Hoffman, M.W.; (submitted). Machine Learning with Physics Knowledge for Prediction: A Survey, Transactions on Machine Learning Research (TMLR).
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    Carvalho, J.; Le, A.T.; Jahr, P. ; Sun, Q. ; Urain, J.; Koert, D.; Peters, J. (submitted). Grasp Diffusion Network: Learning Grasp Generators from Partial Point Clouds with Diffusion Models in SO(3)xR3, Submitted to the IEEE Robotics and Automation Letters (R-AL).
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    Palenicek, D.; Lutter, M.; Carvalho, J.; Dennert, D.; Ahmad, F.; Peters, J. (submitted). Diminishing Return of Value Expansion Methods, Submitted to the IEEE Transaction on Pattern Analysis and Machine Intelligence (PAMI).
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    Carvalho, J.; Le, A.T.; Kicki, P. ; Koert, D.; Peters, J. (submitted). Motion Planning Diffusion: Learning and Adapting Robot Motion Planning with Diffusion Models, Submitted to the IEEE Transactions on Robotics (T-Ro).
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    Le, A. T.; Hansel, K.; Carvalho, J.; Watson, J.; Urain, J.; Biess, A.; Chalvatzaki, G.; Peters, J. (submitted). Global Tensor Motion Planning, Submitted to the IEEE Robotics and Automation Letters (R-AL).
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    Klink, P.; D'Eramo, C.; Peters, J.; Pajarinen, J. (in press). On the Benefit of Optimal Transport for Curriculum Reinforcement Learning, IEEE Transaction on Pattern Analysis and Machine Intelligence (PAMI).
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    Luis, C.E.; Bottero, A.G.; Vinogradska, J.; Berkenkamp, F.; Peters, J. (in press). Uncertainty Representations in State-Space Layers for Deep Reinforcement Learning under Partial Observability, Transactions on Machine Learning Research (TMLR).
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    Prasad, V.; Heitlinger, L; Koert, D.; Stock-Homburg, R.; Peters, J.; Chalvatzaki, G. (conditionally accepted). Learning Multimodal Latent Dynamics for Human-Robot Interaction, Submitted to the IEEE Transaction of Robotics (T-RO).
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    Liu, P.; Bou-Ammar H.; Peters, J.; Tateo D. (conditionally accepted). Safe Reinforcement Learning on the Constraint Manifold: Theory and Applications, Submitted to the IEEE Transactions on Robotics (T-Ro).
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    Urain, J.; Mandlekar, A.; Du, Y.; Shafiullah, M.; Xu, D.; Fragkiadaki, K.; Chalvatzaki, G.; Peters, J. (conditionally accepted). Deep Generative Models in Robotics: A Survey on Learning from Multimodal Demonstrations, IEEE Transactions on Robotics (T-RO).
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    Vincent, T.; Palenicek, D.; Belousov, B.; Peters, J.; D'Eramo, C. (2025). Iterated Q-Network: Beyond One-Step Bellman Updates in Deep Reinforcement Learning, Transactions on Machine Learning Research (TMLR).
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    Funk, N.; Chen, C.; Schneider, T.; Chalvatzaki, G.; Calandra, R.; Peters, J. (2025). On the Importance of Tactile Sensing for Imitation Learning: A Case Study on Robotic Match Lighting, ICRA 2025 Workshop on “Towards Human Level Intelligence Vision and Tactile Sensing”.
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    Huang, J.; Tateo, D.; Liu, P.; Peters, J. (2025). Adaptive Control based Friction Estimation for Tracking Control of Robot Manipulators, IEEE Robotics and Automation Letters, and IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 10, pp.2454-2461.
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    Chowdhury, A.; Maurer, H.; Kshirsagar, A.; Ploeger, K.; Peters, J.; Mueller, H. (2025). The Earlier You Know, the Smoother You Act, Conference of the Human Movement Science Section of the German Association of Sports Science.
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    Dam, T.; D'Eramo, C.; Peters, J.; Pajarinen, J. (2024). A Unified Perspective on Value Backup and Exploration in Monte-Carlo Tree Search, Journal of Artificial Intelligence Research (JAIR), 81, pp.511-577.
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    Abdulsamad, H.; Nickl, P.; Klink, P.; Peters, J. (2024). Variational Hierarchical Mixtures for Probabilistic Learning of Inverse Dynamics, IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 46, 4, pp.1950-1963.
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    Kicki, P.; Liu, P.; Tateo, D.; Bou Ammar, H.; Walas, K.; Skrzypczynski, P.; Peters, J. (2024). Fast Kinodynamic Planning on the Constraint Manifold with Deep Neural Networks, IEEE Transactions on Robotics (T-Ro), and Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 40, pp.277-297.
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    Prasad, V.; Kshirsagar, A; Koert, D.; Stock-Homburg, R.; Peters, J.; Chalvatzaki, G. (2024). MoVEInt: Mixture of Variational Experts for Learning Human-Robot Interactions from Demonstrations, IEEE Robotics and Automation Letters (RA-L), 9, 7, pp.6043--6050.
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    Weng, Y.; Chun, S.; Ohashi, M.; Matsuda, T.; Sekimoria, Y.; Pajarinen, J.; Peters, J.; Maki, T. (2024). Autonomous Underwater Vehicle Link Alignment Control in Unknown Environments Using Reinforcement Learning, Journal of Field Robotics, 41, 6, pp.1724--1743.
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    Holzmann, P.; Maik Pfefferkorn, M.; Peters, J.; Findeisen, R. (2024). Learning Energy-Efficient Trajectory Planning for Robotic Manipulators using Bayesian Optimization, Proceedings of the European Control Conference (ECC).
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    Gu, S.; Liu, P.; Kshirsagar, A.; Chen, G.; Peters, J.; Knoll, A. (2024). ROSCOM: Robust Safe Reinforcement Learning on Stochastic Constraint Manifolds, IEEE Transactions on Automation Science and Engineering (T-ASE).
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    Herrmann, F.; Zach, S.B.; Banfi, J.; Peters, J.; Chalvatzaki, G.; Tateo, D. (2024). Safe and Efficient Path Planning under Uncertainty via Deep Collision Probability Fields, IEEE Robotics and Automation Letters (RA-L).
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    Al-Hafez, F.; Zhao, G.; Peters, J.; Tateo, D. (2024). Time-Efficient Reinforcement Learning with Stochastic Stateful Policies, European Workshop on Reinforcement Learning (EWRL).
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    Luis, C.E.; Bottero, A.G.; Vinogradska, J.; Berkenkamp, F.; Peters, J. (2024). Value-Distributional Model-Based Reinforcement Learning, Journal of Machine Learning Research (JMLR), 25, 298, pp.1-42.
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    Guenster, J.; Liu, P.; Peters, J.; Tateo, D. (2024). Handling Long-Term Safety and Uncertainty in Safe Reinforcement Learning, Proceedings of the Conference on Robot Learning (CoRL).
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    Kicki, P.; Tateo; D., Liu, P.; Guenster, J.; Peters, J.; Walas, K. (2024). Bridging the gap between Learning-to-plan, Motion Primitives and Safe Reinforcement Learning, Proceedings of the Conference on Robot Learning (CoRL).
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    Lenz, J.; Gruner, T.; Palenicek, D.; Schneider, T.; Pfenning, I.; Peters J. (2024). Analysing the Interplay of Vision and Touch for Dexterous Insertion Tasks, CoRL 2024 Workshop on Learning Robot Fine and Dexterous Manipulation: Perception and Control.
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    Liu, Y.; Belousov, B.; Schneider, T.; Harsono, K.; Cheng, T.W.; Shih, S.G.; Tessmann, O.; Peters, J. (2024). Advancing Sustainable Construction: Discrete Modular Systems & Robotic Assembly, Sustainability, 16, pp.6678, MDPI.
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    Buechler, D.; Calandra, R.; Peters, J. (2023). Learning to Control Highly Accelerated Ballistic Movements on Muscular Robots, Robotics and Autonomous Systems, 159, 104230.
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    Lutter, M.; Peters, J. (2023). Combining Physics and Deep Learning to learn Continuous-Time Dynamics Models, International Journal of Robotics Research (IJRR), 42, 3.
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    Lutter, M.; Belousov, B.; Mannor, S.; Fox, D.; Garg, A.; Peters, J. (2023). Continuous-Time Fitted Value Iteration for Robust Policies, IEEE Transaction on Pattern Analysis and Machine Intelligence (PAMI).
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    Loeckel, S.; Ju, S.; Schaller, M.; van Vliet, P.; Peters, J. (2023). An Adaptive Human Driver Model for Realistic Race Car Simulations, IEEE Transactions on Systems, Man and Cybernetics: Systems (TSMC), 53, 11, pp.6718-6730.
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    Look, A.; Kandemir, M.; Rakitsch, B.; Peters, J. (2023). A Deterministic Approximation to Neural SDEs, IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 45, 4, pp.4023-4037.
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    Bjelonic, F.; Lee, J.; Arm, P.; Sako, D.; Tateo, D.; Peters, J.; Hutter, M. (2023). Learning-Based Design and Control for Quadrupedal Robots With Parallel-Elastic Actuators, IEEE Robotics and Automation Letters (R-AL), 8, 3, pp.1611-1618.
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    Urain, J.; Li, A.; Liu, P.; D'Eramo, C.; Peters, J. (2023). Composable energy policies for reactive motion generation and reinforcement learning, International Journal of Robotics Research (IJRR).
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    Abdulsamad, H.; Peters, J. (2023). Model-Based Reinforcement Learning via Stochastic Hybrid Models, IEEE Open Journal of Control Systems, Special Section: Intersection of Machine Learning with Control, 2, pp.155 - 170, IEEE.
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    Ju, S.; van Vliet, P.; Arenz, O.; Peters, J. (2023). Digital Twin of a Driver-in-the-Loop Race Car Simulation with Contextual Reinforcement Learning, IEEE Robotics and Automation Letters (RA-L), 8, 7, pp.4107-4114.
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    Peters, S.; Peters, J.; Findeisen, R. (2023). Quantifying Uncertainties along the Automated Driving Stack, ATZ worldwide volume, 125, pp.62-65.
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    Flynn, H.; Reeb, D.; Kandemir, M.; Peters, J. (2023). PAC-Bayes Bounds for Bandit Problems: A Survey and Experimental Comparison, IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 45, 12, pp.15308-15327.
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    Look, A.; Kandemir, M.; Rakitsch, B.; Peters, J. (2023). Cheap and Deterministic Inference for Deep State-Space Models of Interacting Dynamical Systems, Transactions on Machine Learning Research (TMLR).
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    Gu, S.; Kshirsagar, A.; Du Y.; Chen G.; Peters J.; Knoll A. (2023). A Human-Centered Safe Robot Reinforcement Learning Framework with Interactive Behaviors, Frontiers in Neurorobotics, 17, 1280341.
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    Parisi, S.; Tateo, D.; Hensel, M.; D'Eramo, C.; Peters, J.; Pajarinen, J. (2022). Long-Term Visitation Value for Deep Exploration in Sparse-Reward Reinforcement Learning, Algorithms, 15, 3, pp.81.
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    Akrour, R.; Tateo, D.; Peters, J. (2022). Continuous Action Reinforcement Learning from a Mixture of Interpretable Experts, IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 44, 10, pp.6795-6806.
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    Loeckel, S.; Kretschi, A.; van Vliet, P.; Peters, J. (2022). Identification and modelling of race driving styles, Vehicle System Dynamics, 60, 8, pp.2890--2918.
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    Tosatto, S.; Carvalho, J.; Peters, J. (2022). Batch Reinforcement Learning with a Nonparametric Off-Policy Policy Gradient, IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 44, 10, pp.5996--6010.
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    Belousov, B.; Wibranek, B.; Schneider, J.; Schneider, T.; Chalvatzaki, G.; Peters, J.; Tessmann, O. (2022). Robotic Architectural Assembly with Tactile Skills: Simulation and Optimization, Automation in Construction, 133, pp.104006.
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    Funk, N.; Schaff, C.; Madan, R.; Yoneda, T.; Urain, J.; Watson, J.; Gordon, E.; Widmaier, F; Bauer, S.; Srinivasa, S.; Bhattacharjee, T.; Walter, M.; Peters, J. (2022). Benchmarking Structured Policies and Policy Optimization for Real-World Dexterous Object Manipulation, IEEE Robotics and Automation Letters (R-AL).
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    Muratore, F.; Ramos, F.; Turk, G.; Yu, W.; Gienger, M.; Peters, J. (2022). Robot Learning from Randomized Simulations: A Review, Frontiers in Robotics and AI, 9.
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    You, B.; Arenz, O.; Chen, Y.; Peters, J. (2022). Integrating Contrastive Learning with Dynamic Models for Reinforcement Learning from Images, Neurocomputing.
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    Flynn, H.; Reeb, D.; Kandemir, M.; Peters, J. (2022). PAC-Bayesian Lifelong Learning For Multi-Armed Bandits, Data Mining and Knowledge Discovery, 36, 2, pp.841-876.
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    Prasad, V.; Stock-Homburg, R.; Peters, J. (2022). Human-Robot Handshaking: A Review, International Journal of Social Robotics (IJSR), 14, 1, pp.277-293.
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    Zheng, Y.; Veiga, F.F.; Peters, J.; Santos, V.J. (2022). Autonomous Learning of Page Flipping Movements via Tactile Feedback, IEEE Transactions on Robotics (T-Ro), 38, 5, pp.2734 - 2749.
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    Hansel, K.; Moos, J.; Abdulsamad, H.; Stark, S.; Clever, D.; Peters, J. (2022). Robust Reinforcement Learning: A Review of Foundations and Recent Advances, Machine Learning and Knowledge Extraction (MAKE), 4, 1, pp.276--315, MDPI.
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    Weng, Y.; Pajarinen, J.; Akrour, R.; Matsuda, T.; Peters, J.; Maki, T. (2022). Reinforcement Learning Based Underwater Wireless Optical Communication Alignment for Multiple Autonomous Underwater Vehicles, IEEE Journal of Oceanic Engineering, 47, 4, pp.1231-1245.
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    Buechler, D.; Guist, S.; Calandra, R.; Berenz, V.; Schoelkopf, B.; Peters, J. (2022). Learning to Play Table Tennis From Scratch using Muscular Robots, IEEE Transactions on Robotics (T-Ro), 38, 6, pp.3850-3860.
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    Weng, Y.; Matsuda, T.; Sekimuri, Y.; Pajarinen, J.; Peters, J.; Maki, T. (2022). Pointing Error Control of Underwater Wireless Optical Communication on Mobile Platform, IEEE Photonics Technology Letters, 34, 13, pp.699-702.
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    Cowen-Rivers, A.; Lyu, W.; Tutunov, R.; Wang, Z.; Grosnit, A.; Griffiths, R.R.; Maraval, A.; Jianye, H.; Wang, J.; Peters, J.; Bou Ammar, H. (2022). HEBO: An Empirical Study of Assumptions in Bayesian Optimisation, Journal of Artificial Intelligence Research, 74, pp.1269-1349.
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    Weng, Y.; Matsuda, T.; Sekimoria, Y.; Pajarinen, J.; Peters, J.; Maki, T. (2022). Establishment of Line-of-Sight Optical Links Between Autonomous Underwater Vehicles: Field Experiment and Performance Validation, Applied Ocean Research, 129.
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    Urain, J.; Tateo, D; Peters, J. (2022). Learning Stable Vector Fields on Lie Groups, Robotics and Automation Letters (RA-L).
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    Dam, T.; Chalvatzaki, G.; Peters, J.; Pajarinen, J. (2022). Monte-carlo robot path planning, IEEE Robotics and Automation Letters (RA-L), 7, 4, pp.11213-11220.
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    Muratore, F.; Gienger, M.; Peters, J. (2021). Assessing Transferability from Simulation to Reality for Reinforcement Learning, IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 43, 4, pp.1172-1183, IEEE.
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    Rawal, N.; Koert, D.; Turan, C.; Kersting, K.; Peters, J.; Stock-Homburg, R. (2021). ExGenNet: Learning to Generate Robotic Facial Expression Using Facial Expression Recognition, Frontiers in Robotics & AI, 8, 730317.
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    Tosatto, S.; Akrour, R.; Peters, J. (2021). An Upper Bound of the Bias of Nadaraya-Watson Kernel Regression under Lipschitz Assumptions, Stats, 4, pp.1--17.
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    Muratore, F.; Eilers, C.; Gienger, M.; Peters, J. (2021). Data-efficient Domain Randomization with Bayesian Optimization, IEEE Robotics and Automation Letters (RA-L), with Presentation at the IEEE International Conference on Robotics and Automation (ICRA), IEEE.
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    Hoefer, S.; Bekris, K.; Handa, A.; Gamboa, J.C.; Golemo, F.; Mozifian, M.; Atkeson, C.G., Fox, D.; Goldberg, K.; Leonard, J.; Liu, C.K.; Peters, J.; Song, S.; Welinder, P.; White, M. (2021). Sim2Real in Robotics and Automation: Applications and Challenges, IEEE Transactions on Automation Science (T-ASE), 18, 2, pp.398-400.
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    Akrour, R.; Atamna, A.; Peters, J. (2021). Convex Optimization with an Interpolation-based Projection and its Application to Deep Learning, Machine Learning (MACH), 110, 8, pp.2267-2289.
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    Klink, P.; Abdulsamad, H.; Belousov, B.; D'Eramo, C.; Peters, J.; Pajarinen, J. (2021). A Probabilistic Interpretation of Self-Paced Learning with Applications to Reinforcement Learning, Journal of Machine Learning Research (JMLR).
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    Tanneberg, D.; Ploeger, K.; Rueckert, E.; Peters, J. (2021). SKID RAW: Skill Discovery from Raw Trajectories, IEEE Robotics and Automation Letters (RA-L).
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    Lampariello, R.; Mishra, H.; Oumer, N.W.; Peters, J. (2021). Robust Motion Prediction of a Free-Tumbling Satellite with On-Ground Experimental Validation, Journal of Guidance, Control, and Dynamics, 44, 10, pp.1777-1793.
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    Bustamante, S.; Peters, J.; Schoelkopf, B.; Grosse-Wentrup, M.; Jayaram, V. (2021). ArmSym: a virtual human-robot interaction laboratory for assistive robotics, IEEE Transactions on Human-Machine Systems, 51, 6, pp.568-577.
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    D`Eramo, C.; Tateo, D; Bonarini, A.; Restelli, M.; Peters, J. (2021). MushroomRL: Simplifying Reinforcement Learning Research, Journal of Machine Learning Research (JMLR), 22, 131, pp.1-5.
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    Veiga, F. F.; Edin B.B; Peters, J. (2020). Grip Stabilization through Independent Finger Tactile Feedback Control, Sensors (Special Issue on Sensors and Robot Control), 20.
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    Vinogradska, J.; Bischoff, B.; Koller, T.; Achterhold, J.; Peters, J. (2020). Numerical Quadrature for Probabilistic Policy Search, IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 42, 1, pp.164-175.
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    Lioutikov, R.; Maeda, G.; Veiga, F.F.; Kersting, K.; Peters, J. (2020). Learning Attribute Grammars for Movement Primitive Sequencing, International Journal of Robotics Research (IJRR), 39, 1, pp.21-38.
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    Gomez-Gonzalez, S.; Neumann, G.; Schoelkopf, B.; Peters, J. (2020). Adaptation and Robust Learning of Probabilistic Movement Primitives, IEEE Transactions on Robotics (T-Ro), 36, 2, pp.366-379.
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    Koert, D.; Trick, S.; Ewerton, M.; Lutter, M.; Peters, J. (2020). Incremental Learning of an Open-Ended Collaborative Skill Library, International Journal of Humanoid Robotics (IJHR), 17, 1.
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    Loeckel, S.; Peters, J.; van Vliet, P. (2020). A Probabilistic Framework for Imitating Human Race Driver Behavior, IEEE Robotics and Automation Letters (RA-L), with Presentation at the IEEE International Conference on Robotics and Automation (ICRA), 5, 2.
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    Gomez-Gonzalez, S.; Prokudin, S.; Schoelkopf, B.; Peters, J. (2020). Real Time Trajectory Prediction Using Deep Conditional Generative Models, IEEE Robotics and Automation Letters (ICRA/RA-L), with Presentation at the IEEE International Conference on Robotics and Automation (ICRA), 5, 2, pp.970-976.
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    Ewerton, M.; Arenz, O.; Peters, J. (2020). Assisted Teleoperation in Changing Environments with a Mixture of Virtual Guides, Advanced Robotics, 34.
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    Lauri, M.; Pajarinen, J.; Peters, J.; Frintrop, S. (2020). Multi-Sensor Next-Best-View Planning as Matroid-Constrained Submodular Maximization, IEEE Robotics and Automation Letters (RA-L), 5, 4, pp.5323-5330.
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    Agudelo-Espana, D.; Gomez-Gonzalez, S.; Bauer, S.; Schoelkopf, B.; Peters, J. (2020). Bayesian Online Prediction of Change Points, Conference on Uncertainty in Artificial Intelligence (UAI).
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    Koert, D.; Kircher, M.; Salikutluk, V.; D'Eramo, C.; Peters, J. (2020). Multi-Channel Interactive Reinforcement Learning for Sequential Tasks, Frontiers in Robotics and AI Human-Robot Interaction.
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    Veiga, F. F.; Akrour, R.; Peters, J. (2020). Hierarchical Tactile-Based Control Decomposition of Dexterous In-Hand Manipulation Tasks, Frontiers in Robotics and AI.
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    Koc, O.; Peters, J. (2019). Learning to serve: an experimental study for a new learning from demonstrations framework, IEEE Robotics and Automation Letters (ICRA/RA-L), with Presentation at the IEEE International Conference on Robotics and Automation (ICRA).
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    Brandherm, F.; Peters, J.; Neumann, G.; Akrour, R. (2019). Learning Replanning Policies with Direct Policy Search, IEEE Robotics and Automation Letters (RA-L).
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    Parisi, S.; Tangkaratt, V.; Peters, J.; Khan, M. E. (2019). TD-Regularized Actor-Critic Methods, Machine Learning (MLJ), 108, 8, pp.1467-1501.
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    Koc, O.; Maeda, G.; Peters, J. (2019). Optimizing the Execution of Dynamic Robot Movements with Learning Control, IEEE Transactions on Robotics, 35, 4, pp.1552-3098.
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    Belousov, B.; Peters, J. (2019). Entropic Regularization of Markov Decision Processes, Entropy, 21, 7, MDPI.
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    Pajarinen, J.; Thai, H.L.; Akrour, R.; Peters, J.; Neumann, G. (2019). Compatible natural gradient policy search, Machine Learning (MLJ), 108, 8, pp.1443--1466, Springer.
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    Celemin, C.; Maeda, G.; Peters, J.; Ruiz-del-Solar, J.; Kober, J. (2019). Reinforcement Learning of Motor Skills using Policy Search and Human Corrective Advice, International Journal of Robotics Research (IJRR), 38, 14.
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    Gomez Gonzalez, S.; Nemmour, Y.; Schoelkopf, B.; Peters, J. (2019). Reliable Real Time Ball Tracking for Robot Table Tennis, Robotics, 8, 4.
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    Schuermann, T.; Mohler, B.J.; Peters, J.; Beckerle, P. (2019). How Cognitive Models of Human Body Experience Might Push Robotics, Frontiers in Neurorobotics.
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    Kroemer, O.; Leischnig, S.; Luettgen, S.; Peters, J. (2018). A Kernel-based Approach to Learning Contact Distributions for Robot Manipulation Tasks, Autonomous Robots (AURO), 42, 3, pp.581-600.
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    Paraschos, A.; Daniel, C.; Peters, J.; Neumann, G. (2018). Using Probabilistic Movement Primitives in Robotics, Autonomous Robots (AURO), 42, 3, pp.529-551.
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    Yi, Z.; Zhang, Y.; Peters, J. (2018). Biomimetic Tactile Sensors and Signal Processing with Spike Trains: A Review, Sensors & Actuators: A. Physical, 269, pp.41-52.
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    Paraschos, A.; Rueckert, E.; Peters, J.; Neumann, G. (2018). Probabilistic Movement Primitives under Unknown System Dynamics, Advanced Robotics (ARJ), 32, 6, pp.297-310.
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    Manschitz, S.; Gienger, M.; Kober, J.; Peters, J. (2018). Mixture of Attractors: A novel Movement Primitive Representation for Learning Motor Skills from Demonstrations, IEEE Robotics and Automation Letters (RA-L), 3, 2, pp.926-933.
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    Vinogradska, J.; Bischoff, B.; Peters, J. (2018). Approximate Value Iteration based on Numerical Quadrature, Proceedings of the International Conference on Robotics and Automation, and IEEE Robotics and Automation Letters (RA-L), 3, pp.1330-1337.
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    Osa, T.; Pajarinen, J.; Neumann, G.; Bagnell, J.A.; Abbeel, P.; Peters, J. (2018). An Algorithmic Perspective on Imitation Learning, Foundations and Trends in Robotics.
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    Veiga, F.; Peters, J.; Hermans, T. (2018). Grip Stabilization of Novel Objects using Slip Prediction, IEEE Transactions on Haptics, 11, 4, pp.531--542.
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    Koc, O.; Maeda, G.; Peters, J. (2018). Online optimal trajectory generation for robot table tennis, Robotics and Autonomous Systems (RAS).
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    Buechler, D.; Calandra, R.; Schoelkopf, B.; Peters, J. (2018). Control of Musculoskeletal Systems using Learned Dynamics Models, IEEE Robotics and Automation Letters, and IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
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    Sosic, A.; Rueckert, E.; Peters, J.; Zoubir, A.M.; Koeppl, H (2018). Inverse Reinforcement Learning via Nonparametric Spatio-Temporal Subgoal Modeling, Journal of Machine Learning Research (JMLR), 19, 69, pp.1--45.
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    Osa, T.; Peters, J.; Neumann, G. (2018). Hierarchical Reinforcement Learning of Multiple Grasping Strategies with Human Instructions, Advanced Robotics, 32, 18, pp.955-968.
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    Kupcsik, A.G.; Deisenroth, M.P.; Peters, J.; Ai Poh, L.; Vadakkepat, V.; Neumann, G. (2017). Model-based Contextual Policy Search for Data-Efficient Generalization of Robot Skills, Artificial Intelligence, 247, pp.415-439.
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    Wang, Z.; Boularias, A.; Muelling, K.; Schoelkopf, B.; Peters, J. (2017). Anticipatory Action Selection for Human-Robot Table Tennis, Artificial Intelligence, 247, pp.399-414.
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    Maeda, G.; Neumann, G.; Ewerton, M.; Lioutikov, R.; Kroemer, O.; Peters, J. (2017). Probabilistic Movement Primitives for Coordination of Multiple Human-Robot Collaborative Tasks, Autonomous Robots (AURO), 41, 3, pp.593-612.
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    Parisi, S.; Pirotta, M.; Peters, J. (2017). Manifold-based Multi-objective Policy Search with Sample Reuse, Neurocomputing, 263, pp.3-14.
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    Maeda, G.; Ewerton, M.; Neumann, G.; Lioutikov, R.; Peters, J. (2017). Phase Estimation for Fast Action Recognition and Trajectory Generation in Human-Robot Collaboration, International Journal of Robotics Research (IJRR), 36, 13-14, pp.1579-1594.
  •     Bib
    Padois, V.; Ivaldib, S.; Babič, J.; Mistry, M.; Peters, J.; Nori, F. (2017). Whole-body multi-contact motion in humans and humanoids, Robotics and Autonomous Systems, 90, pp.97-117.
  •     Bib
    Ivaldi, S.; Lefort, S.; Peters, J.; Chetouani, M.; Provasi, J.; Zibetti, E. (2017). Towards Engagement Models that Consider Individual Factors in HRI: On the Relation of Extroversion and Negative Attitude Towards Robots to Gaze and Speech During a Human-Robot Assembly Task, International Journal of Social Robotics, 9, pp.63-86.
  •     Bib
    Yi, Z.; Zhang, Y.; Peters, J. (2017). Bioinspired Tactile Sensor for Surface Roughness Discrimination, Sensors and Actuators A: Physical, 255, pp.46-53.
  •     Bib
    Osa, T.; Ghalamzan, E. A. M.; Stolkin, R.; Lioutikov, R.; Peters, J.; Neumann, G. (2017). Guiding Trajectory Optimization by Demonstrated Distributions, IEEE Robotics and Automation Letters (RA-L), 2, 2, pp.819-826, IEEE.
  •     Bib
    Kroemer, O.; Peters, J. (2017). A Comparison of Autoregressive Hidden Markov Models for Multi-Modal Manipulations with Variable Masses, Proceedings of the International Conference of Robotics and Automation, and IEEE Robotics and Automation Letters (RA-L), 2, 2, pp.1101 - 1108.
  •     Bib
    Lioutikov, R.; Neumann, G.; Maeda, G.; Peters, J. (2017). Learning Movement Primitive Libraries through Probabilistic Segmentation, International Journal of Robotics Research (IJRR), 36, 8, pp.879-894.
  •     Bib
    Paraschos, A.; Lioutikov, R.; Peters, J.; Neumann, G. (2017). Probabilistic Prioritization of Movement Primitives, Proceedings of the International Conference on Intelligent Robot Systems, and IEEE Robotics and Automation Letters (RA-L).
  •     Bib
    van Hoof, H.; Tanneberg, D.; Peters, J. (2017). Generalized Exploration in Policy Search, Machine Learning (MLJ), 106, 9-10, pp.1705-1724.
  •     Bib
    van Hoof, H.; Neumann, G.; Peters, J. (2017). Non-parametric Policy Search with Limited Information Loss, Journal of Machine Learning Research (JMLR), 18, 73, pp.1-46.
  •     Bib
    Vinogradska, J.; Bischoff, B.; Nguyen-Tuong, D.; Peters, J. (2017). Stability of Controllers for Gaussian Process Forward Models, Journal of Machine Learning Research (JMLR), 18, 100, pp.1-37.
  •     Bib
    Dermy, O.; Paraschos, A.; Ewerton, M.; Charpillet, F.; Peters, J.; Ivaldi, S (2017). Prediction of intention during interaction with iCub with Probabilistic Movement Primitives, Frontiers in Robotics and AI, 4, pp.45.
  •       Bib
    Rueckert, E.; Kappel, D.; Tanneberg, D.; Pecevski, D; Peters, J. (2016). Recurrent Spiking Networks Solve Planning Tasks, Nature PG: Scientific Reports, 6, 21142, Nature Publishing Group.
  •     Bib
    Maeda, G.; Ewerton, M.; Koert, D; Peters, J. (2016). Acquiring and Generalizing the Embodiment Mapping from Human Observations to Robot Skills, IEEE Robotics and Automation Letters (RA-L), 1, 2, pp.784--791.
  •     Bib
    Daniel, C.; Neumann, G.; Kroemer, O.; Peters, J. (2016). Hierarchical Relative Entropy Policy Search, Journal of Machine Learning Research (JMLR), 17, pp.1-50.
  •     Bib
    Abdolmaleki, A.; Lau, N.; Reis, L.; Peters, J.; Neumann, G. (2016). Contextual Policy Search for Linear and Nonlinear Generalization of a Humanoid Walking Controller, Journal of Intelligent & Robotic Systems.
  •     Bib
    Daniel, C.; van Hoof, H.; Peters, J.; Neumann, G. (2016). Probabilistic Inference for Determining Options in Reinforcement Learning, Machine Learning (MLJ), 104, 2-3, pp.337-357.
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    Yi, Z.; Zhang, Y.; Peters, J. (2016). Surface Roughness Discrimination Using Bioinspired Tactile Sensors, Proceedings of the 16th International Conference on Biomedical Engineering.
  •       Bib
    Calandra, R.; Seyfarth, A.; Peters, J.; Deisenroth, M. (2015). Bayesian Optimization for Learning Gaits under Uncertainty, Annals of Mathematics and Artificial Intelligence (AMAI).
  •     Bib
    Mariti, C.; Muscolo, G.G.; Peters, J.; Puig, D.; Recchiuto, C.T.; Sighieri, C.; Solanas, A.; von Stryk, O. (2015). Developing biorobotics for veterinary research into cat movements, Journal of Veterinary Behavior: Clinical Applications and Research, 10, pp.248-254.
  •     Bib
    Daniel, C.; Kroemer, O.; Viering, M.; Metz, J.; Peters, J. (2015). Active Reward Learning with a Novel Acquisition Function, Autonomous Robots (AURO), 39, pp.389-405.
  •     Bib
    Manschitz, S.; Kober, J.; Gienger, M.; Peters, J. (2015). Learning Movement Primitive Attractor Goals and Sequential Skills from Kinesthetic Demonstrations, Robotics and Autonomous Systems, 74, pp.97-107.
  •     Bib
    Lioutikov, R.; Paraschos, A.; Peters, J.; Neumann, G. (2014). Generalizing Movements with Information Theoretic Stochastic Optimal Control, Journal of Aerospace Information Systems, 11, 9, pp.579-595.
  •     Bib
    Neumann, G.; Daniel, C.; Paraschos, A.; Kupcsik, A.; Peters, J. (2014). Learning Modular Policies for Robotics, Frontiers in Computational Neuroscience.
  •     Bib
    Dann, C.; Neumann, G.; Peters, J. (2014). Policy Evaluation with Temporal Differences: A Survey and Comparison, Journal of Machine Learning Research (JMLR), 15, March, pp.809-883.
  •       Bib
    Meyer, T.; Peters, J.; Zander, T.O.; Schoelkopf, B.; Grosse-Wentrup, M. (2014). Predicting Motor Learning Performance from Electroencephalographic Data, Journal of Neuroengineering and Rehabilitation, 11, 1.
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    Bocsi, B.; Csato, L.; Peters, J. (2014). Indirect Robot Model Learning for Tracking Control, Advanced Robotics.
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    Ben Amor, H.; Saxena, A.; Hudson, N.; Peters, J. (2014). Special issue on autonomous grasping and manipulation, Autonomous Robots (AURO).
  •     Bib
    Wierstra, D.; Schaul, T.; Glasmachers, T.; Sun, Y.; Peters, J.; Schmidhuber, J. (2014). Natural Evolution Strategies, Journal of Machine Learning Research (JMLR), 15, March, pp.949-980.
  •     Bib
    Muelling, K.; Boularias, A.; Schoelkopf, B.; Peters, J. (2014). Learning Strategies in Table Tennis using Inverse Reinforcement Learning, Biological Cybernetics, 108, 5, pp.603-619.
  •       Bib
    van Hoof, H.; Kroemer, O; Peters, J. (2014). Probabilistic Segmentation and Targeted Exploration of Objects in Cluttered Environments, IEEE Transactions on Robotics (TRo), 30, 5, pp.1198-1209.
  •       Bib
    Muelling, K.; Kober, J.; Kroemer, O.; Peters, J. (2013). Learning to Select and Generalize Striking Movements in Robot Table Tennis, International Journal of Robotics Research (IJRR), 32, 3, pp.263-279.
  •       Bib
    Wang, Z.; Muelling, K.; Deisenroth, M. P.; Ben Amor, H.; Vogt, D.; Schoelkopf, B.; Peters, J. (2013). Probabilistic Movement Modeling for Intention Inference in Human-Robot Interaction, International Journal of Robotics Research (IJRR), 32, 7, pp.841-858.
  •       Bib
    Kober, J.; Bagnell, D.; Peters, J. (2013). Reinforcement Learning in Robotics: A Survey, International Journal of Robotics Research (IJRR), 32, 11, pp.1238-1274.
  •       Bib
    Englert, P.; Paraschos, A.; Peters, J.;Deisenroth, M.P. (2013). Probabilistic Model-based Imitation Learning, Adaptive Behavior Journal, 21, pp.388-403.
  •       Bib
    Deisenroth, M. P.; Neumann, G.; Peters, J. (2013). A Survey on Policy Search for Robotics, Foundations and Trends in Robotics, 21, pp.388-403.
  •       Bib
    Lampert, C.H.; Peters, J. (2012). Real-Time Detection of Colored Objects In Multiple Camera Streams With Off-the-Shelf Hardware Components, Journal of Real-Time Image Processing, 7, 1, pp.31-41.
  •       Bib
    Kober, J.; Wilhelm, A.; Oztop, E.; Peters, J. (2012). Reinforcement Learning to Adjust Parametrized Motor Primitives to New Situations, Autonomous Robots (AURO), 33, 4, pp.361-379, Springer US.
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    Nguyen-Tuong, D.; Peters, J. (2012). Online Kernel-based Learning for Task-Space Tracking Robot Control, IEEE Transactions on Neural Networks and Learning Systems, 23, 9, pp.1417-1425 .
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    Piater, J.; Jodogne, S.; Detry, R.; Kraft, D.; Krueger, N.; Kroemer, O.; Peters, J. (2011). Learning Visual Representations for Perception-Action Systems, International Journal of Robotics Research (IJRR), 30, 3, pp.294-307.
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    Detry, R.; Kraft, D.; Kroemer, O.; Peters, J.; Krueger, N.; Piater, J.; (2011). Learning Grasp Affordance Densities, Paladyn Journal of Behavioral Robotics, 2, 1, pp.1-17.
  •       Bib
    Kober, J.; Peters, J. (2011). Policy Search for Motor Primitives in Robotics, Machine Learning (MLJ), 84, 1-2, pp.171-203.
  •     Bib
    Nguyen Tuong, D.; Peters, J. (2011). Incremental Sparsification for Real-time Online Model Learning, Neurocomputing, 74, 11, pp.1859-1867.
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    Gomez Rodriguez, M.; Peters, J.; Hill, J.; Schoelkopf, B.; Gharabaghi, A.; Grosse-Wentrup, M. (2011). Closing the Sensorimotor Loop: Haptic Feedback Helps Decoding of Motor Imagery, Journal of Neuroengineering, 8, 3.
  •     Bib
    Kroemer, O.; Lampert, C.H.; Peters, J. (2011). Learning Dynamic Tactile Sensing with Robust Vision-based Training, IEEE Transactions on Robotics (T-Ro), 27, 3, pp.545-557.
  •       Bib
    Muelling, K.; Kober, J.; Peters, J. (2011). A Biomimetic Approach to Robot Table Tennis, Adaptive Behavior Journal, 19, 5.
  •       Bib
    Hachiya, H.; Peters, J.; Sugiyama, M. (2011). Reward Weighted Regression with Sample Reuse for Direct Policy Search in Reinforcement Learning, Neural Computation, 23, 11.
  •     Bib
    Nguyen Tuong, D.; Peters, J. (2011). Model Learning in Robotics: a Survey, Cognitive Processing, 12, 4.
  •     Bib
    Wierstra, D.; Foerster, A.; Peters, J.; Schmidhuber, J. (2010). Recurrent Policy Gradients, Logic Journal of the IGPL, 18, pp.620-634.
  •       Bib
    Kober, J.; Peters, J. (2010). Imitation and Reinforcement Learning - Practical Algorithms for Motor Primitive Learning in Robotics, IEEE Robotics and Automation Magazine, 17, 2, pp.55-62.
  •       Bib
    Kroemer, O.; Detry, R.; Piater, J.; Peters, J. (2010). Combining Active Learning and Reactive Control for Robot Grasping, Robotics and Autonomous Systems, 58, 9, pp.1105-1116.
  •     Bib
    Sehnke, F.; Osendorfer, C.; Rueckstiess, T.; Graves, A.; Peters, J.; Schmidhuber, J. (2010). Parameter-exploring Policy Gradients, Neural Networks, 23.
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    Morimura, T.; Uchibe, E.; Yoshimoto, J.; Peters, J.; Doya, K. (2010). Derivatives of Logarithmic Stationary Distributions for Policy Gradient Reinforcement Learning, Neural Computation, 22, 2.
  •     Bib
    Peters, J.;Kober, J.;Schaal, S. (2010). Policy learning algorithmis for motor learning (Algorithmen zum automatischen Erlernen von Motorfaehigkigkeiten), Automatisierungstechnik, 58, 12, pp.688-694.
  •     Bib
    Hachiya, H.; Akiyama, T.; Sugiyama, M.; Peters, J. (2009). Adaptive Importance Sampling for Value Function Approximation in Off-policy Reinforcement Learning, Neural Networks, 22, 10, pp.1399-1410.
  •     Bib
    Deisenroth, M.P.; Rasmussen, C.E.; Peters, J. (2009). Gaussian Process Dynamic Programming, Neurocomputing, 72, pp.1508-1524.
  •     Bib
    Peters, J.; Ng, A. (2009). Guest Editorial: Special Issue on Robot Learning, Part B, Autonomous Robots (AURO), 27, 2.
  •     Bib
    Nguyen Tuong, D.; Seeger, M.; Peters, J. (2009). Model Learning with Local Gaussian Process Regression, Advanced Robotics, 23, 15, pp.2015-2034.
  •     Bib
    Kober, J.; Peters, J. (2009). Reinforcement Learning fuer Motor-Primitive, Kuenstliche Intelligenz.
  •     Bib
    Peters, J.; Morimoto, J.; Tedrake, R.; Roy, N. (2009). Robot Learning, IEEE Robotics & Automation Magazine, 16, 3, pp.19-20.
  •     Bib
    Peters, J.; Ng, A. (2009). Guest Editorial: Special Issue on Robot Learning, Part A, Autonomous Robots (AURO), 27, 1.
  •     Bib
    Steinke, F.; Hein, M.; Peters, J.; Schoelkopf, B (2008). Manifold-valued Thin-Plate Splines with Applications in Computer Graphics, Computer Graphics Forum (Special Issue on Eurographics 2008), 27, 2.
  •     Bib
    Nakanishi, J.;Cory, R.;Mistry, M.;Peters, J.;Schaal, S. (2008). Operational space control: A theoretical and empirical comparison, International Journal of Robotics Research (IJRR), 27, 6, pp.737-757.
  •     Bib
    Peters, J. (2008). Machine Learning for Motor Skills in Robotics, Kuenstliche Intelligenz, 3.
  •     Bib
    Peters, J.; Schaal, S. (2008). Natural actor critic, Neurocomputing, 71, 7-9, pp.1180-1190.
  •     Bib
    Peters, J.; Schaal, S. (2008). Learning to control in operational space, International Journal of Robotics Research (IJRR), 27, pp.197-212.
  •     Bib
    Peters, J.; Schaal, S. (2008). Reinforcement learning of motor skills with policy gradients, Neural Networks, 21, 4, pp.682-97.
  •     Bib
    Peters, J.;Mistry, M.;Udwadia, F. E.;Nakanishi, J.;Schaal, S. (2008). A unifying framework for robot control with redundant DOFs, Autonomous Robots (AURO), 24, 1, pp.1-12.
  •   Bib
    Peters, J. (2007). Computational Intelligence: By Amit Konar, The Computer Journal, 50, 6, pp.758.
  •     Bib
    Nakanishi, J.; Mistry, M.; Peters, J.; Schaal, S. (2007). Experimental evaluation of task space position/orientation control towards compliant control for humanoid robots, IEEE International Conference on Intelligent Robotics Systems (IROS 2007).
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    Peters, J. (1998). Fuzzy Logic for Practical Applications, Kuenstliche Intelligenz (KI), 4, pp.60.

Conference and Workshop Papers

  •       Bib
    Kienle, C.; Alt, B.; Katic, D.; Jäkel, R.; Peters, J. (2025). QueryCAD: Grounded Question Answering for CAD Models, IEEE International Conference on Robotics and Automation (ICRA).
  •     Bib
    Vincent, T.; Wahren, F.; Peters, J.; Belousov, B.; D'Eramo, C. (2025). Adaptive Q-Network: On-the-fly Target Selection for Deep Reinforcement Learning, International Conference on Learning Representations (ICLR).
  •       Bib
    Diwan, A.A.; Urain, J.; Kober, J.; Peters, J. (2025). Noise-conditioned Energy-based Annealed Rewards (NEAR): A Generative Framework for Imitation Learning from Observation, International Conference on Learning Representations (ICLR).
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    Straub, D.; Niehues, T.F.; Peters, J.; Rothkopf, C.A. (2025). Inverse decision-making using neural amortized Bayesian actors, International Conference on Learning Representations (ICLR).
  •     Bib
    Duret, G.; Bourennane, Y.; Mazurak, D.; Samsonenko, A.; Zara, F.; Chen, L.; Peters, J. (2025). Facilitate and scale up the creation of 3D meshes and 6D category-based datasets with generative models: GenVegeFruits, Proceedings of the IEEE International Conference on Image Processing (ICIP).
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    Palenicek, D.; Vogt, F.; Peters, J. (2025). Scaling Off-Policy Reinforcement Learning with Batch and Weight Normalization, Multi-disciplinary Conference on Reinforcement Learning and Decision Making (RLDM).
  •     Bib
    Bohlinger, N.; Peters, J. (2025). Massively Scaling Explicit Policy-conditioned Value Functions, Multi-disciplinary Conference on Reinforcement Learning and Decision Making (RLDM).
  •       Bib
    Bohlinger, N.; Czechmanowski, G.; Krupka, M.; Kicki, P.; Walas, K.; Peters, J.; Tateo, D. (2025). Morphology-Aware Legged Locomotion with Reinforcement Learning, German Robotics Conference (GRC).
  •       Bib
    Carvalho, J.; Le, A.; Jahr, P. ; Sun, Q. ; Urain, J.; Koert, D.; Peters, J. (2025). Grasp Diffusion Network: Learning Grasp Generators from Partial Point Clouds with Diffusion Models in SO(3)×R3, German Robotics Conference (GRC).
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    Chen, J.; Kshirsagar, A.; Heller, F.; Gomez Andreu, M.; Belousov, B.; Schneider, T.; Lin, L. P. Y.; Doerschner, K.; Drewing, K.; Peters, J. (2025). Active Sampling for Hardness Classification with Vision-Based Tactile Sensors, German Robotics Conference (GRC).
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    Nonnengiesser, F.; Kshirsagar, A.; Belousov, B.; Peters, J. (2025). Visuotactile In-Hand Pose Estimation, German Robotics Conference (GRC).
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    Nguyen, D.H.; Schneider, T.; Duret, G.; Kshirsagar, A.; Belousov, B.; Peters, J. (2025). TacEx: GelSight Tactile Simulation in Isaac Sim – Combining Soft-Body and Visuotactile Simulators, German Robotics Conference (GRC).
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    Vincent, T.; Faust, T.; Tripathi, Y.; Peters, J.; D'Eramo, C. (2025). Eau De Q-Network: Adaptive Distillation of Neural Networks in Deep Reinforcement Learning, Conference on Reinforcement Learning and Decision Making (RLDM).
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    Pompetzki, K.; Le, A. T.; Gruner, T.; Watson, J.; Chalvatzaki, G.; Peters, J. (2025). Geometrically-Aware Goal Inference: Leveraging Motion Planning as Inference, German Robotics Conference (GRC).
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    Lenz, J.; Pfenning, I.; Gruner, T.; Palenicek, D.; Schneider, T.; Peters, J. (2025). Exploring the Role of Vision and Touch in Reinforcement Learning for Dexterous Insertion Tasks, Multi-disciplinary Conference on Reinforcement Learning and Decision Making (RLDM).
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    Celik, O.; Li, Z.; Blessing, D.; Li, G.; Palenicek, D.; Peters, J.; Chalvatzaki, G.; Neumann, G. (2025). Diffusion-Based Maximum Entropy Reinforcement Learning, 7th Robot Learning Workshop: Towards Robots with Human-Level Abilities (ICLR).
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    Scherer, C. F.; Tölle, M.; Gruner, T.; Palenicek, D.; Schneider, T.; Schramowski, P.; Belousov, B.; Peters, J. (2025). AllmAN: A German Vision-Language-Action Model, German Robotics Conference (GRC).
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    Toelle, M.; Gruner, T.; Palenicek, D.; Guenster, J.; Liu, P.; Watson, J.; Tateo, D.; Peters, J. (2025). Towards Safe Robot Foundation Models, German Robotics Conference (GRC).
  •     Bib
    Schneider, T.; de Farias, C.; Calandra, R.; Chen L.; Peters, J. (2025). Active Perception for Tactile Sensing: A Task-Agnostic Attention-Based Approach, German Robotics Conference (GRC).
  •       Bib
    Bohlinger, N.; Kinzel, J.; Palenicek, D.; Antczak, L.; Peters, J. (2025). Gait in Eight: Efficient On-Robot Learning for Omnidirectional Quadruped Locomotion, Under review.
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    Stasica, M.; Bick, A.; Bohlinger, N.; Mohseni, O.; Fritzsche, J.; Hübler, C.; Peters, J.; Seyfarth, A. (2025). Bridge the Gap: Enhancing Quadruped Locomotion with Vertical Ground Perturbations, Under review.
  •     Bib
    Le, A.T.; Pompetzki, K.; Peters, J.; Biess, A. (2025). Kinematics Correspondence As Inexact Graph Matching, German Robotics Conference (GRC).
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    Koosha, T. A.; Kshirsagar, A.; Augustat, N.; Hahne, F.; Mühl, D.; Melzig, C. A.; Bremmer, F.; Peters, J.; Endres, D. M. (2025). Staring Down the Elevator Shaft: Postural Responses to Virtual Heights in an Indoor Environment, Proceedings of the Annual Meeting of the Cognitive Science Society (CogSci).
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    Bhatt, A.; Palenicek, D.; Belousov, B.; Argus, M.; Amiranashvili, A.; Brox, T.; Peters, J. (2024). CrossQ: Batch Normalization in Deep Reinforcement Learning for Greater Sample Efficiency and Simplicity, International Conference on Learning Representations (ICLR), Spotlight.
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    Derstroff, C.; Brugger, J.; Cerrato, M.; Peters, J.; Kramer, S. (2024). Peer Learning: Learning Complex Policies in Groups from Scratch via Action Recommendations, Proceedings of the National Conference on Artificial Intelligence (AAAI).
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    Vincent, T.; Metelli, A.; Belousov, B.; Peters, J.; Restelli, M.; D'Eramo, C. (2024). Parameterized Projected Bellman Operator, Proceedings of the National Conference on Artificial Intelligence (AAAI).
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    Tiboni, G.; Klink, P.; Peters, J.; Tommasi, T.; D'Eramo, C.; Chalvatzaki, G. (2024). Domain Randomization via Entropy Maximization, International Conference on Learning Representations (ICLR).
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    Hahne, F.; Prasad V.; Kshirsagar A.; Koert D.; Stock-Homburg R. M.; Peters J.; Chalvatzaki G. (2024). Transition State Clustering for Interaction Segmentation and Learning, ACM/IEEE International Conference on Human Robot Interaction (HRI), Late Breaking Report.
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    Goeksu, Y.; Almeida-Correia, A.; Prasad, V.; Kshirsagar, A.; Koert, D.; Peters, J.; Chalvatzaki, G. (2024). Kinematically Constrained Human-like Bimanual Robot-to-Human Handovers, ACM/IEEE International Conference on Human Robot Interaction (HRI), Late Breaking Report.
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    Hendawy, A.; Peters, J.; D'Eramo, C. (2024). Multi-Task Reinforcement Learning with Mixture of Orthogonal Experts, International Conference on Learning Representations (ICLR).
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    Reddi, A.; Toelle, M.; Peters, J.; Chalvatzaki, G.; D'Eramo, C. (2024). Robust Adversarial Reinforcement Learning via Bounded Rationality Curricula, International Conference on Learning Representations (ICLR), Spotlight.
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    Boehm, A.; Schneider, T.; Belousov, B.; Kshirsagar, A.; Lin, L.; Doerschner, K.; Drewing, K.; Rothkopf, C.A.; Peters, J. (2024). What Matters for Active Texture Recognition With Vision-Based Tactile Sensors, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA).
  •       Bib
    Spartakov, R.; Kshirsagar, A.; Mühl, D.; Schween, R.; Endres, D.M.; Bremmer, F.; Melzig, C.; Peters, J. (2024). Balancing on the Edge: Review and Computational Framework on the Dynamics of Fear of Falling and Fear of Heights in Postural Control, Proceedings of the Annual Meeting of the Cognitive Science Society (CogSci).
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    Wiebe, F.; Turcato, N.; Dalla Libera, A.; Zhang, C.; Vincent, T.; Vyas, S.; Giacomuzzo, G.; Carli, R.; Romeres, D.; Sathuluri, A.; Zimmermann, M.; Belousov, B.; Peters, J.; Kirchner, F.; Kumar, S. (2024). Reinforcement Learning for Athletic Intelligence: Lessons from the 1st “AI Olympics with RealAIGym” Competition, The 33rd International Joint Conference on Artificial Intelligence.
  •     Bib
    Lin, L.; Boehm, A.; Belousov, B.; Kshirsagar, A.; Schneider, T.; Peters, J.; Doerschner, K.; Drewing, K. (2024). Task-Adapted Single-Finger Explorations of Complex Objects, Eurohaptics.
  •     Bib
    Nguyen, D.M.H.; Lukashina, N.; Nguyen, N.; Le, A.T.; Nguyen, T.T.; Ho, N.; Peters, J.; Sonntag, D.; Zaverkin, V.; Niepert, M. (2024). Structure-Aware E(3)-Invariant Molecular Conformer Aggregation Networks, Proceedings of the International Conference on Machine Learning (ICML).
  •     Bib
    Palenicek, D.; Gruner, T.; Schneider, T.; Böhm, A.; Lenz, J.; Pfenning, I. and Krämer, E.; Peters, J. (2024). Learning Tactile Insertion in the Real World, IEEE ICRA 2024 Workshop on Robot Embodiment through Visuo-Tactile Perception.
  •     Bib
    Vincent, T.; Wahren, F.; Peters, J.; Belousov, B.; D'Eramo, C.; (2024). Adaptive Q-Network: On-the-fly Target Selection for Deep Reinforcement Learning, European Workshop on Reinforcement Learning (EWRL).
  •     Bib
    Vincent, T.; Wahren, F.; Peters, J.; Belousov, B.; D'Eramo, C.; (2024). Adaptive Q-Network: On-the-fly Target Selection for Deep Reinforcement Learning, ICML Workshop on Automated Reinforcement Learning.
  •       Bib
    Bohlinger, N.; Czechmanowski, G.; Krupka, M.; Kicki, P.; Walas, K.; Peters, J.; Tateo, D. (2024). One Policy to Run Them All: an End-to-end Learning Approach to Multi-Embodiment Locomotion, Conference on Robot Learning (CoRL).
  •     Bib
    Geiss, H.J.; Al-Hafez, F.; Seyfarth, A.; Peters, J.; Tateo, D. (2024). Exciting Action: Investigating Efficient Exploration for Learning Musculoskeletal Humanoid Locomotion, IEEE-RAS International Conference on Humanoid Robots (Humanoids).
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    Jansonnie, P.; Wu, B.; Perez, J.; Peters J. (2024). Unsupervised Skill Discovery for Robotic Manipulation through Automatic Task Generation, IEEE-RAS International Conference on Humanoid Robots (Humanoids).
  •     Bib
    Nguyen, D.H.M.*; Le, A.T.*; Nguyen, T.Q.; Nghiem, T.D.; Duong-Tran, D. ; Peters, J.; Li, S.; Niepert, M.; Sonntag, D. (2024). Dude: Dual Distribution-Aware Context Prompt Learning For Large Vision-Language Model, Asian Conference on Machine Learning (ACML).
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    Watson, J.; Hahner, B.; Belousov, B.; Peters, J. (2024). Tractable Bayesian Dynamics Priors from Differentiable Physics for Learning and Control, 40th Anniversary of the IEEE International Conference on Robotics and Automation (ICRA@40).
  •     Bib
    Palenicek, D.; Gruner, T.; Schneider, T.; Böhm, A.; Lenz, J.; Pfenning, I. and Krämer, E.; Peters, J. (2024). Learning Tactile Insertion in the Real World, 40th Anniversary of the IEEE International Conference on Robotics and Automation (ICRA@40).
  •     Bib
    Bhatt, A.; Palenicek, D.; Belousov, B.; Argus, M.; Amiranashvili, A.; Brox, T.; Peters, J. (2024). CrossQ: Batch Normalization in Deep Reinforcement Learning for Greater Sample Efficiency and Simplicity, European Workshop on Reinforcement Learning (EWRL).
  •     Bib
    Kshirsagar, A.; Heller, F.; Gomez Andreu, M.; Belousov, B.; Schneider, T.; Lin, L. P. Y.; Doerschner, K.; Drewing, K.; Peters, J. (2024). Hardness Similarity Detection Using Vision-Based Tactile Sensors, 40th Anniversary of the IEEE International Conference on Robotics and Automation (ICRA@40).
  •     Bib
    Becker, N.; Sovailo, K.; Zhu, C.; Gattung, E.; Hansel, K.; Schneider, T.; Zhu, Y.; Hasegawa, Y.; Peters, J. (2024). Integrating and Evaluating Visuo-tactile Sensing with Haptic Feedback for Teleoperated Robot Manipulation, 40th Anniversary of the IEEE International Conference on Robotics and Automation (ICRA@40).
  •     Bib
    Qian, C.; Urain, J.; Zakka, K.; Peters, J. (2024). PianoMime: Learning a Generalist, Dexterous Piano Player from Internet Demonstrations, Conference on Robot Learning (CoRL).
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    Gomez Andreu, M.A.; Ploeger, K.; Peters, J. (2024). Beyond the Cascade: Juggling Vanilla Siteswap Patterns, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
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    Prasad, V.; Kshirsagar, A; Koert, D.; Stock-Homburg, R.; Peters, J.; Chalvatzaki, G. (2024). MoVEInt: Mixture of Variational Experts for Learning HRI from Demonstrations, Workshop on Nonverbal Cues for Human-Robot Cooperative Intelligence at IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
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    Prasad, V.; Kshirsagar, A; Koert, D.; Stock-Homburg, R.; Peters, J.; Chalvatzaki, G. (2024). MoVEInt: Mixture of Variational Experts for Learning Human-Robot Interactions from Demonstrations, Workshop on Structural Priors as Inductive Biases for Learning Robot Dynamics at Robotics: Science and Systems (RSS).
  •       Bib
    Helmut, E.; Dziarski, L.; Funk, N.; Belousov, B.; Peters, J. (2024). Learning Force Distribution Estimation for the GelSight Mini Optical Tactile Sensor Based on Finite Element Analysis, 2nd NeurIPS Workshop on Touch Processing: From Data to Knowledge.
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    Le, A. T.; Hansel, K.; Carvalho, J.; Urain, J.; Biess, A.; Chalvatzaki, G.; Peters, J. (2024). Global Tensor Motion Planning, CoRL 2024 Workshop on Differentiable Optimization Everywhere.
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    Nguyen, D.H.; Schneider, T.; Duret, G.; Kshirsagar, A.; Belousov, B.; Peters, J. (2024). TacEx: GelSight Tactile Simulation in Isaac Sim – Combining Soft-Body and Visuotactile Simulators, CoRL 2024 Workshop on Learning Robot Fine and Dexterous Manipulation: Perception and Control.
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    Kornmann, M.; He, Q.; Kshirsagar, A.; Ploeger, K.; Peters, J. (2024). Learning to Accurately Throw Paper Planes, CoRL 2024 Workshop on Learning Robot Fine and Dexterous Manipulation: Perception and Control.
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    Meser, M.; Bhatt, A.; Belousov, B.; Peters, J. (2024). MuJoCo MPC for Humanoid Control: Evaluation on HumanoidBench, 40th Anniversary of the IEEE International Conference on Robotics and Automation (ICRA@40).
  •       Bib
    Bohlinger, N.; Czechmanowski, G.; Krupka, M.; Kicki, P.; Walas, K.; Peters, J.; Tateo, D. (2024). One Policy to Run Them All: an End-to-end Learning Approach to Multi-Embodiment Locomotion, CoRL 2024 Workshop on Morphology-Aware Policy and Design Learning Workshop.
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    Drolet, M.; Stepputtis, S.; Kailas, S.; Jain, A.; Schaal, S.; Peters, J.; Ben Amor, H. (2024). A Comparison of Imitation Learning Algorithms for Bimanual Manipulation, CoRL 2024 Workshop on Whole-body Control and Bimanual Manipulation.
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    Funk, N.; Urain, J.; Carvalho, J.; Prasad, V.; Chalvatzaki, G.; Peters, J. (2024). ACTIONFLOW: Equivariant, Accurate, and Efficient Manipulation Policies with Flow Matching, CoRL 2024 Workshop on Mastering Robot Manipulation in a World of Abundant Data.
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    Kaidanov, O.; Al-Hafez, F.; Süvari, Y.; Belousov, B.; Peters, J. (2024). The Role of Domain Randomization in Training Diffusion Policies for Whole-Body Humanoid Control, CoRL 2024 Workshop on Whole-body Control and Bimanual Manipulation: Applications in Humanoids and Beyond.
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    Faust, T.L.; Maraqten, H.; Aghadavoodi, E.; Belousov, B.; Peters, J. (2024). Velocity-History-Based Soft Actor-Critic: Tackling IROS'24 Competition AI Olympics with RealAIGym, IROS'24 Competition AI Olympics with RealAIGym.
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    Bohlinger, N.; Czechmanowski, G.; Krupka, M.; Kicki, P.; Walas, K.; Peters, J.; Tateo, D. (2024). One Policy to Run Them All: Towards an End-to-end Learning Approach to Multi-Embodiment Locomotion, RSS 2024 Workshop on Embodiment-Aware Robot Learning.
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    Bohlinger, N.; Tateo, D.; Kicki, P.; Walas, K.; Peters, J. (2024). Benefits of an Actuated Spine in Agile Quadruped Locomotion, ICRA 2024 Workshop on Bio-inspired Robotics and Robotics for Biology.
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    Liu, P.; Guenster, J.; Funk, N.; Groeger, S.; Chen, D.; Bou Ammar, H.; Jankowski, J.; Maric, A.; Calinon, S.; et, al.; Lioutikov, R.; Neumann, G.; Likmeta, A.; Zhalehmehrabi, A.; Bonenfant, T.; Restelli, M.; Tateo, D.; Liu, Z.; Peters, R. (2024). A Retrospective on the Robot Air Hockey Challenge: Benchmarking Robust, Reliable, and Safe Learning Techniques for Real-world Robotics, Advances in Neural Information Processing Systems.
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    Toelle, M.; Belousov, B.; Peters, J. (2023). A Unifying Perspective on Language-Based Task Representations for Robot Control, CoRL Workshop on Language and Robot Learning: Language as Grounding.
  •     Bib
    Liu, Y.; Belousov, B.; Funk, N.; Chalvatzaki, G.; Peters, J.; Tessman, O. (2023). Auto(mated)nomous Assembly, International Conference on Trends on Construction in the Post-Digital Era, pp.167-181, Springer, Cham.
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    Liu, P.; Zhang, K.; Tateo, D.; Jauhri, S.; Hu, Z.; Peters, J. Chalvatzaki, G. (2023). Safe Reinforcement Learning of Dynamic High-Dimensional Robotic Tasks: Navigation, Manipulation, Interaction, 2023 IEEE International Conference on Robotics and Automation (ICRA), IEEE.
  •     Bib
    Zhu, Y.; Nazirjonov, S.; Jiang, B.; Colan, J.; Aoyama, T.; Hasegawa, Y.; Belousov, B.; Hansel, K.; Peters, J. (2023). Visual Tactile Sensor Based Force Estimation for Position-Force Teleoperation, IEEE International Conference on Cyborg and Bionic Systems (CBS), pp.49-52.
  •     Bib
    Zelch, C.; Peters, J.; von Stryk, C. (2023). Start State Selection for Control Policy Learning from Optimal Trajectories, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA).
  •       Bib
    Urain, J.; Funk, N.; Peters, J.; Chalvatzaki G (2023). SE(3)-DiffusionFields: Learning smooth cost functions for joint grasp and motion optimization through diffusion, International Conference on Robotics and Automation (ICRA).
  •       Bib
    Hansel, K.; Urain, J.; Peters, J.; Chalvatzaki, G. (2023). Hierarchical Policy Blending as Inference for Reactive Robot Control, 2023 IEEE International Conference on Robotics and Automation (ICRA), IEEE.
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    Le, A. T.; Hansel, K.; Peters, J.; Chalvatzaki, G. (2023). Hierarchical Policy Blending As Optimal Transport, 5th Annual Learning for Dynamics & Control Conference (L4DC), PMLR.
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    Luis, C.; Bottero, A.G.; Vinogradska, J.; Berkenkamp, F.; Peters, J. (2023). Model-Based Uncertainty in Value Functions, Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS).
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    Al-Hafez, F.; Tateo, D.; Arenz, O.; Zhao, G.; Peters, J. (2023). LS-IQ: Implicit Reward Regularization for Inverse Reinforcement Learning, International Conference on Learning Representations (ICLR).
  •     Bib
    Palenicek, D.; Lutter, M.; Carvalho, J.; Peters, J. (2023). Diminishing Return of Value Expansion Methods in Model-Based Reinforcement Learning, International Conference on Learning Representations (ICLR).
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    Buechler, D.; Guist, S.; Calandra, R.; Berenz, V.; Schoelkopf, B.; Peters, J. (2023). Learning to Play Table Tennis From Scratch using Muscular Robots, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), IEEE T-TRo Track.
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    Urain, J.; Tateo, D.; Peters, J. (2023). Learning Stable Vector Fields on Lie Groups, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), IEEE R-AL Track.
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    Bethge, J.; Pfefferkorn, M.; Rose, A.; Peters, J.; Findeisen, R. (2023). Model predictive control with Gaussian-process-supported dynamical constraints for autonomous vehicles, Proceedings of the 22nd World Congress of the International Federation of Automatic Control.
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    Carvalho, J.; Le, A. T.; Baierl, M.; Koert, D.; Peters, J. (2023). Motion Planning Diffusion: Learning and Planning of Robot Motions with Diffusion Models, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
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    Funk, N.; Mueller, P.-O.; Belousov, B.; Savchenko, A.; Findeisen, R.; Peters, J. (2023). High-Resolution Pixelwise Contact Area and Normal Force Estimation for the GelSight Mini Visuotactile Sensor Using Neural Networks, Embracing Contacts-Workshop at ICRA 2023.
  •     Bib
    Vincent, T.; Belousov, B.; D'Eramo, C.; Peters, J. (2023). Iterated Deep Q-Network: Efficient Learning of Bellman Iterations for Deep Reinforcement Learning, European Workshop on Reinforcement Learning (EWRL).
  •       Bib
    Al-Hafez, F.; Tateo, D.; Arenz, O.; Zhao, G.; Peters, J. (2023). Least Squares Inverse Q-Learning, European Workshop on Reinforcement Learning (EWRL).
  •     Bib
    Flynn, H.; Reeb, D.; Kandemir, M.; Peters, J. (2023). Improved Algorithms for Stochastic Linear Bandits Using Tail Bounds for Martingale Mixtures, Advances in Neural Information Processing Systems (NIPS / NeurIPS).
  •     Bib
    Gruner, T.; Belousov, B.; Muratore, F.; Palenicek, D.; Peters, J. (2023). Pseudo-Likelihood Inference, Advances in Neural Information Processing Systems (NIPS / NeurIPS).
  •       Bib
    Le, A. T.; Chalvatzaki, G.; Biess, A.; Peters, J. (2023). Accelerating Motion Planning via Optimal Transport, Advances in Neural Information Processing Systems (NIPS / NeurIPS).
  •     Bib
    Le, A. T.; Chalvatzaki, G.; Biess, A.; Peters, J. (2023). Accelerating Motion Planning via Optimal Transport, IROS 2023 Workshop on Differentiable Probabilistic Robotics: Emerging Perspectives on Robot Learning, [Oral].
  •     Bib
    Rother, D.; Weisswange, T.H.; Peters, J. (2023). Disentangling Interaction using Maximum Entropy Reinforcement Learning in Multi-Agent Systems, European Conference on Artificial Intelligence (ECAI).
  •     Bib
    Vincent, T.; Metelli, A.; Peters, J.; Restelli, M.; D'Eramo, C. (2023). Parameterized projected Bellman operator, ICML Workshop on New Frontiers in Learning, Control, and Dynamical Systems.
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    Metternich, H.; Hendawy, A.; Klink, P.; Peters, J.; D'Eramo, C. (2023). Using Proto-Value Functions for Curriculum Generation in Goal-Conditioned RL, NeurIPS 2023 Workshop on Goal-Conditioned Reinforcement Learning.
  •     Bib
    Le, A. T.; Chalvatzaki, G.; Biess, A.; Peters, J. (2023). Accelerating Motion Planning via Optimal Transport, NeurIPS 2023 Workshop Optimal Transport and Machine Learning, [Oral].
  •     Bib
    Boehm, A.; Schneider, T.; Belousov, B.; Kshirsagar, A.; Lin, L.; Doerschner, K.; Drewing, K.; Rothkopf, C.A.; Peters, J. (2023). Tactile Active Texture Recognition With Vision-Based Tactile Sensors, NeurIPS Workshop on Touch Processing: a new Sensing Modality for AI.
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    Watson, J.; Peters, J.; (2023). Sample-Efficient Online Imitation Learning using Pretrained Behavioural Cloning Policies, NeurIPS 6th Robot Learning Workshop: Pretraining, Fine-Tuning, and Generalization with Large Scale Models.
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    Al-Hafez, F.; Zhao, G.; Peters, J.; Tateo, D. (2023). LocoMuJoCo: A Comprehensive Imitation Learning Benchmark for Locomotion, Robot Learning Workshop, Conference on Neural Information Processing Systems (NeurIPS).
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    Lach, L.; Haschke, R.; Tateo, D.; Peters, J.; Ritter, H.; Sol, J.; Torras, C. (2023). Towards Transferring Tactile-based Continuous Force Control Policies from Simulation to Robot, NeurIPS 2023 Workshop on Touch Processing.
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    Zelch, C.; Peters, J.; von Stryk, O. (2023). Clustering of Motion Trajectories by a Distance Measure Based on Semantic Features, Proceedings of the IEEE International Conference on Humanoid Robots (Humanoids).
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    Klink, P.; D`Eramo, C.; Peters, J.; Pajarinen, J. (2022). Boosted Curriculum Reinforcement Learning, International Conference on Learning Representations (ICLR).
  •     Bib
    Memmel, M.; Liu, P.; Tateo, D.; Peters, J. (2022). Dimensionality Reduction and Prioritized Exploration for Policy Search, 25th International Conference on Artificial Intelligence and Statistics (AISTATS).
  •     Bib
    Palenicek, D.; Lutter, M., Peters, J. (2022). Revisiting Model-based Value Expansion, Multi-disciplinary Conference on Reinforcement Learning and Decision Making (RLDM).
  •     Bib
    Klink, P.; Yang, H.; D'Eramo, C.; Peters, J.; Pajarinen, J. (2022). Curriculum Reinforcement Learning via Constrained Optimal Transport, International Conference on Machine Learning (ICML).
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    Urain, J.*; Le, A.T.*; Lambert, A.*; Chalvatzaki, G.; Boots, B.; Peters, J. (2022). Learning Implicit Priors for Motion Optimization, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
  •     Bib
    Liu, P.; Zhang, K.; Tateo, D.; Jauhri, S.; Peters, J.; Chalvatzaki, G.; (2022). Regularized Deep Signed Distance Fields for Reactive Motion Generation, 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
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    Zheng, Y.; Veiga, F.F.; Peters, J.; Santos, V.J. (2022). Autonomous Learning of Page Flipping Movements via Tactile Feedback, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
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    Funk, N.; Menzenbach, S.; Chalvatzaki, G.; Peters, J. (2022). Graph-based Reinforcement Learning meets Mixed Integer Programs: An application to 3D robot assembly discovery, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
  •     Bib
    Ploeger, K.; Peters, J. (2022). Controlling the Cascade: Kinematic Planning for N-ball Toss Juggling, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
  •       Bib
    Schneider, T.; Belousov, B.; Chalvatzaki, G.; Romeres, D.; Jha, D.K.; Peters, J. (2022). Active Exploration for Robotic Manipulation, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
  •       Bib
    Schneider, T.; Belousov, B.; Abdulsamad, H.; Peters, J. (2022). Active Inference for Robotic Manipulation, 5th Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM).
  •     Bib
    Galljamov, R.; Zhao, G.; Belousov, B.; Seyfarth, A.; Peters, J. (2022). Improving Sample Efficiency of Example-Guided Deep Reinforcement Learning for Bipedal Walking, 2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids).
  •     Bib
    Watson, J.; Peters, J. (2022). Inferring Smooth Control: Monte Carlo Posterior Policy Iteration with Gaussian Processes, Conference on Robot Learning (CoRL).
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    Carvalho, J.; Koert, D.; Daniv, M.; Peters, J. (2022). Adapting Object-Centric Probabilistic Movement Primitives with Residual Reinforcement Learning, 2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids).
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    Vorndamme, J.; Carvalho, J.; Laha, R.; Koert, D.; Figueredo, L.; Peters, J.; Haddadin, S. (2022). Integrated Bi-Manual Motion Generation and Control shaped for Probabilistic Movement Primitives, 2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids).
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    Prasad, V.; Koert, D.; Stock-Homburg, R.; Peters, J.; Chalvatzaki, G. (2022). MILD: Multimodal Interactive Latent Dynamics for Learning Human-Robot Interaction, IEEE-RAS International Conference on Humanoid Robots (Humanoids).
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    Siebenborn, M.; Belousov, B.; Huang, J.; Peters, J. (2022). How Crucial is Transformer in Decision Transformer?, Foundation Models for Decision Making Workshop at Neural Information Processing Systems.
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    Bottero, A.G.; Luis, C.E.; Vinogradska, J.; Berkenkamp, F.; Peters, J. (2022). Information-Theoretic Safe Exploration with Gaussian Processes, Advances in Neural Information Processing Systems (NIPS / NeurIPS).
  •   Bib
    Le, A. T.; Urain, J.; Lambert, A.; Chalvatzaki, G.; Boots, B.; Peters, J. (2022). Learning Implicit Priors for Motion Optimization, RSS 2022 Workshop on Implicit Representations for Robotic Manipulation.
  •     Bib
    Watson, J.; Lin, J. A.; Klink, P.; Peters, J. (2021). Neural Linear Models with Functional Gaussian Process Priors, 3rd Symposium on Advances in Approximate Bayesian Inference (AABI).
  •     Bib
    Watson, J.; Lin J. A.; Klink, P.; Pajarinen, J.; Peters, J. (2021). Latent Derivative Bayesian Last Layer Networks, Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS).
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    Tosatto, S.; Chalvatzaki, G.; Peters, J. (2021). Contextual Latent-Movements Off-Policy Optimization for Robotic Manipulation Skills, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA).
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    Li, Q.; Chalvatzaki, G.; Peters, J.; Wang, Y. (2021). Directed Acyclic Graph Neural Network for Human Motion Prediction, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA).
  •     Bib
    Prasad, V.; Stock-Homburg, R.; Peters, J. (2021). Learning Human-like Hand Reaching for Human-Robot Handshaking, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA).
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    Lutter, M.; Silberbauer, J.; Watson, J.; Peters, J. (2021). Differentiable Physics Models for Real-world Offline Model-based Reinforcement Learning, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA).
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    Morgan, A.; Nandha, D.; Chalvatzaki, G.; D'Eramo, C.; Dollar, A.; Peters, J. (2021). Model Predictive Actor-Critic: Accelerating Robot Skill Acquisition with Deep Reinforcement Learning, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA).
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    Abdulsamad, H.; Nickl, P.; Klink, P.; Peters, J. (2021). A Variational Infinite Mixture for Probabilistic Inverse Dynamics Learning, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA).
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    Dam, T.; D'Eramo, C.; Peters, J.; Pajarinen J. (2021). Convex Regularization in Monte-Carlo Tree Search, Proceedings of the International Conference on Machine Learning (ICML).
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    Carvalho, J., Tateo, D., Muratore, F., Peters, J. (2021). An Empirical Analysis of Measure-Valued Derivatives for Policy Gradients, International Joint Conference on Neural Networks (IJCNN).
  •     Bib
    Lutter, M.; Mannor, S.; Peters, J.; Fox, D.; Garg, A. (2021). Value Iteration in Continuous Actions, States and Time, International Conference on Machine Learning (ICML).
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    Lutter, M.; Mannor, S.; Peters, J.; Fox, D.; Garg, A. (2021). Robust Value Iteration for Continuous Control Tasks, Robotics: Science and Systems (RSS).
  •     Bib
    Urain, J.; Li, A.; Liu, P.; D'Eramo, C.; Peters, J. (2021). Composable Energy Policies for Reactive Motion Generation and Reinforcement Learning, Robotics: Science and Systems (RSS).
  •     Bib
    Lutter, M.; Clever, D.; Kirsten, R.; Listmann, K.; Peters, J. (2021). Building Skill Learning Systems for Robotics, Proceedings of the IEEE International Conference on Automation Science and Engineering (CASE).
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    Liu, P.; Tateo, D.; Bou-Ammar, H.; Peters, J. (2021). Efficient and Reactive Planning for High Speed Robot Air Hockey, Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
  •     Bib
    Muratore, F.; Gruner, T.; Wiese, F.; Belousov, B.; Gienger, M.; Peters, J. (2021). Neural Posterior Domain Randomization, Conference on Robot Learning (CoRL).
  •     Bib
    Wibranek, B.; Liu, Y.; Funk, N.; Belousov, B.; Peters, J.; Tessmann, O. (2021). Reinforcement Learning for Sequential Assembly of SL-Blocks: Self-Interlocking Combinatorial Design Based on Machine Learning, Proceedings of the 39th eCAADe Conference.
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    Funk, N.; Chalvatzaki, G.; Belousov, B.; Peters, J. (2021). Learn2Assemble with Structured Representations and Search for Robotic Architectural Construction, Conference on Robot Learning (CoRL).
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    Liu, P.; Tateo, D.; Bou-Ammar, H.; Peters, J. (2021). Robot Reinforcement Learning on the Constraint Manifold, Proceedings of the Conference on Robot Learning (CoRL).
  •     Bib
    Bauer, S.; Wüthrich, W.; Widmaier, F.; Buchholz, A.; Stark, S.; Goyal, A.; Steinbrenner, T.; Akpo, J.; Joshi, S.; Berenz, V.; Agrawal, V.; Funk, N.; Urain, J.; Peters, J.; Watson, J.; Et, A.L.l (2021). Real Robot Challenge: A Robotics Competition in the Cloud, Advances in Neural Information Processing Systems (NIPS / NeurIPS).
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    Dam, T.; Klink, P.; D'Eramo, C.; Peters, J.; Pajarinen, J. (2020). Generalized Mean Estimation in Monte-Carlo Tree Search, Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI).
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    Motokura, K.; Takahashi, M.; Ewerton, M.; Peters, J. (2020). Plucking Motions for Tea Harvesting Robots Using Probabilistic Movement Primitives, IEEE Robotics and Automation Letters (ICRA/RA-L), with Presentation at the IEEE International Conference on Robotics and Automation (ICRA), 5, 2, pp.2377-3766.
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    Zelch, C.; Peters, J.; von Stryk, O. (2020). Learning Control Policies from Optimal Trajectories, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA).
  •     Bib
    Tosatto, S.; Carvalho, J.; Abdulsamad, H.; Peters, J. (2020). A Nonparametric Off-Policy Policy Gradient, Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics (AISTATS).
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    D`Eramo, C.; Tateo, D.; Bonarini, A.; Restelli, M.; Peters, J. (2020). Sharing Knowledge in Multi-Task Deep Reinforcement Learning, International Conference in Learning Representations (ICLR).
  •     Bib
    Eilers, C.; Eschmann, J.; Menzenbach, R.; Belousov, B.; Muratore, F.; Peters, J. (2020). Underactuated Waypoint Trajectory Optimization for Light Painting Photography, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA).
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    Stock-Homburg, R.; Peters, J.; Schneider, K.; Prasad, V.; Nukovic, L. (2020). Evaluation of the Handshake Turing Test for anthropomorphic Robots, Proceedings of the ACM/IEEE International Conference on Human Robot Interaction (HRI), Late Breaking Report.
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    Almeida Santos, A.; Gil, C.E.M.; Peters, J.; Steinke, F. (2020). Decentralized Data-Driven Tuning of Droop Frequency Controllers, 2020 IEEE PES Innovative Smart Grid Technologies Europe.
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    Laux, M.; Arenz, O.; Pajarinen, J.; Peters, J. (2020). Deep Adversarial Reinforcement Learning for Object Disentangling, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2020).
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    Keller, L.; Tanneberg, D.; Stark, S.; Peters, J. (2020). Model-Based Quality-Diversity Search for Efficient Robot Learning, Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
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    Klink, P.; D'Eramo, C.; Peters, J.; Pajarinen, J. (2020). Self-Paced Deep Reinforcement Learning, Advances in Neural Information Processing Systems (NIPS / NeurIPS).
  •     Bib
    Ploeger, K.; Lutter, M.; Peters, J. (2020). High Acceleration Reinforcement Learning for Real-World Juggling with Binary Rewards, Conference on Robot Learning (CoRL).
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    Prasad, V.; Stock-Homburg, R.; Peters, J. (2020). Advances in Human-Robot Handshaking, International Conference on Social Robotics, Springer.
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    Lutter, M.; Clever, D.; Belousov, B.; Listmann, K.; Peters, J. (2020). Evaluating the Robustness of HJB Optimal Feedback Control, International Symposium on Robotics.
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    Lutter, M.; Silberbauer, J.; Watson, J.; Peters, J. (2020). A Differentiable Newton Euler Algorithm for Multi-body Model Learning, R:SS Structured Approaches to Robot Learning Workshop.
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    Lauri, M.; Pajarinen, J.; Peters, J. (2019). Information gathering in decentralized POMDPs by policy graph improvement, Proceedings of the International Conference on Autonomous Agents and Multiagent Systems (AAMAS).
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    Lutter, M.; Ritter, C.; Peters, J. (2019). Deep Lagrangian Networks: Using Physics as Model Prior for Deep Learning, International Conference on Learning Representations (ICLR).
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    Tosatto, S.; D'Eramo, C.; Pajarinen, J.; Restelli, M.; Peters, J. (2019). Exploration Driven By an Optimistic Bellman Equation, Proceedings of the International Joint Conference on Neural Networks (IJCNN).
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    Akrour, R.; Pajarinen, J.; Neumann, G.; Peters, J. (2019). Projections for Approximate Policy Iteration Algorithms, Proceedings of the International Conference on Machine Learning (ICML).
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    Becker-Ehmck, P.; Peters, J.; van der Smagt, P. (2019). Switching Linear Dynamics for Variational Bayes Filtering, Proceedings of the International Conference on Machine Learning (ICML).
  •     Bib
    Belousov, B.; Abdulsamad, H.; Schultheis, M.; Peters, J. (2019). Belief Space Model Predictive Control for Approximately Optimal System Identification, 4th Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM).
  •     Bib
    Nass, D.; Belousov, B.; Peters, J. (2019). Entropic Risk Measure in Policy Search, Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
  •     Bib
    Ozdenizci, O.; Meyer, T.; Wichmann, F.; Peters, J.; Schoelkopf B.; Cetin, M.; Grosse-Wentrup, M. (2019). Neural Signatures of Motor Skill in the Resting Brain, Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics (SMC).
  •     Bib
    Urain, J.; Peters, J. (2019). Generalized Multiple Correlation Coefficient as a Similarity Measurement between Trajectories, Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
  •     Bib
    Lutter, M.; Peters, J. (2019). Deep Lagrangian Networks for end-to-end learning of energy-based control for under-actuated systems, International Conference on Intelligent Robots and Systems (IROS).
  •     Bib
    Lutter, M.; Peters, J. (2019). Deep Optimal Control: Using the Euler-Lagrange Equation to learn an Optimal Feedback Control Law, Multi-disciplinary Conference on Reinforcement Learning and Decision Making (RLDM).
  •     Bib
    Belousov, B.; Sadybakasov, A.; Wibranek, B.; Veiga, F.; Tessmann, O.; Peters, J. (2019). Building a Library of Tactile Skills Based on FingerVision, Proceedings of the 2019 IEEE-RAS 19th International Conference on Humanoid Robots (Humanoids).
  •     Bib
    Schultheis, M.; Belousov, B.; Abdulsamad, H.; Peters, J. (2019). Receding Horizon Curiosity, Proceedings of the 3rd Conference on Robot Learning (CoRL).
  •     Bib
    Lutter, M.; Belousov, B.; Listmann, K.; Clever, D.; Peters, J. (2019). HJB Optimal Feedback Control with Deep Differential Value Functions and Action Constraints, Conference on Robot Learning (CoRL).
  •     Bib
    Wibranek, B.; Belousov, B.; Sadybakasov, A.; Peters, J.; Tessmann, O. (2019). Interactive Structure: Robotic Repositioning of Vertical Elements in Man-Machine Collaborative Assembly through Vision-Based Tactile Sensing, Proceedings of the 37th eCAADe and 23rd SIGraDi Conference.
  •     Bib
    Klink, P.; Abdulsamad, H.; Belousov, B.; Peters, J. (2019). Self-Paced Contextual Reinforcement Learning, Proceedings of the 3rd Conference on Robot Learning (CoRL).
  •     Bib
    Watson, J.; Abdulsamad, H.; Peters, J. (2019). Stochastic Optimal Control as Approximate Input Inference, Conference on Robot Learning (CoRL).
  •   Bib
    Abdulsamad, H.; Naveh, K.; Peters, J. (2019). Model-Based Relative Entropy Policy Search for Stochastic Hybrid Systems, 4th Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM).
  •     Bib
    Muratore, F.; Gienger, M.; Peters, J. (2019). Assessing Transferability in Reinforcement Learning from Randomized Simulations, Reinforcement Learning and Decision Making (RLDM).
  •   Bib
    Klink, P.; Peters, J. (2019). Measuring Similarities between Markov Decision Processes, 4th Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM).
  •     Bib
    Lioutikov, R.; Maeda, G.; Veiga, F.F.; Kersting, K.; Peters, J. (2018). Inducing Probabilistic Context-Free Grammars for the Sequencing of Robot Movement Primitives, Proceedings of the International Conference on Robotics and Automation (ICRA).
  •     Bib
    Pinsler, R.; Akrour, R.; Osa, T.; Peters, J.; Neumann, G. (2018). Sample and Feedback Efficient Hierarchical Reinforcement Learning from Human Preferences, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA).
  •     Bib
    Belousov, B.; Peters, J. (2018). Entropic Regularization of Markov Decision Processes, 38th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering.
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    Parmas, P.; Doya, K.; Rasmussen, C.; Peters, J. (2018). PIPPS: Flexible Model-Based Policy Search Robust to the Curse of Chaos, Proceedings of the International Conference on Machine Learning (ICML).
  •     Bib
    Akrour, R.; Veiga, F.; Peters, J.; Neumann, G. (2018). Regularizing Reinforcement Learning with State Abstraction, Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
  •     Bib
    Gondaliya, K.D.; Peters, J.; Rueckert, E. (2018). Learning to Categorize Bug Reports with LSTM Networks, Proceedings of the International Conference on Advances in System Testing and Validation Lifecycle.
  •       Bib
    Muratore, F.; Treede, F.; Gienger, M.; Peters, J. (2018). Domain Randomization for Simulation-Based Policy Optimization with Transferability Assessment, Conference on Robot Learning (CoRL).
  •     Bib
    Koert, D.; Trick, S.; Ewerton, M.; Lutter, M.; Peters, J. (2018). Online Learning of an Open-Ended Skill Library for Collaborative Tasks, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
  •     Bib
    Akrour, R.; Peters, J.; Neumann, G. (2018). Constraint-Space Projection Direct Policy Search, European Workshops on Reinforcement Learning (EWRL).
  •     Bib
    Hoelscher, J.; Koert, D.; Peters, J.; Pajarinen, J. (2018). Utilizing Human Feedback in POMDP Execution and Specification, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
  •     Bib
    Belousov, B.; Peters, J. (2018). Mean Squared Advantage Minimization as a Consequence of Entropic Policy Improvement Regularization, European Workshops on Reinforcement Learning (EWRL).
  •     Bib
    Tangkaratt, V.; van Hoof, H.; Parisi, S.; Neumann, G.; Peters, J.; Sugiyama, M. (2017). Policy Search with High-Dimensional Context Variables, Proceedings of the AAAI Conference on Artificial Intelligence (AAAI).
  •     Bib
    Farraj, F. B.; Osa, T.; Pedemonte, N.; Peters, J.; Neumann, G.; Giordano, P.R. (2017). A Learning-based Shared Control Architecture for Interactive Task Execution, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA).
  •     Bib
    Wilbers, D.; Lioutikov, R.; Peters, J. (2017). Context-Driven Movement Primitive Adaptation, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA).
  •     Bib
    End, F.; Akrour, R.; Peters, J.; Neumann, G. (2017). Layered Direct Policy Search for Learning Hierarchical Skills, Proceedings of the International Conference on Robotics and Automation (ICRA).
  •     Bib
    Gabriel, A.; Akrour, R.; Peters, J.; Neumann, G. (2017). Empowered Skills, Proceedings of the International Conference on Robotics and Automation (ICRA).
  •     Bib
    Abdulsamad, H.; Arenz, O.; Peters, J.; Neumann, G. (2017). State-Regularized Policy Search for Linearized Dynamical Systems, Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS).
  •   Bib
    Fiebig, K.H.; Jayaram, V.; Hesse, T.; Blank, A.; Peters, J.; Grosse-Wentrup, M. (2017). Bayesian Regression for Artifact Correction in Electroencephalography, Proceedings of the 7th Graz Brain-Computer Interface Conference.
  •     Bib
    Akrour, R.; Sorokin, D.; Peters, J.; Neumann, G. (2017). Local Bayesian Optimization of Motor Skills, Proceedings of the International Conference on Machine Learning (ICML).
  •     Bib
    Belousov, B.; Neumann, G.; Rothkopf, C.A.; Peters, J. (2017). Catching Heuristics Are Optimal Control Policies, Proceedings of the Karniel Thirteenth Computational Motor Control Workshop.
  •     Bib
    Pajarinen, J.; Kyrki, V.; Koval, M.; Srinivasa, S; Peters, J.; Neumann, G. (2017). Hybrid Control Trajectory Optimization under Uncertainty, Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
  •     Bib
    Parisi, S.; Ramstedt, S.; Peters, J. (2017). Goal-Driven Dimensionality Reduction for Reinforcement Learning, Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS).
  •     Bib
    Tanneberg, D.; Peters, J.; Rueckert, E. (2017). Online Learning with Stochastic Recurrent Neural Networks using Intrinsic Motivation Signals, Proceedings of the Conference on Robot Learning (CoRL).
  •     Bib
    Maeda, G.; Ewerton, M.; Osa, T.; Busch, B.; Peters, J. (2017). Active Incremental Learning of Robot Movement Primitives, Proceedings of the Conference on Robot Learning (CoRL).
  •     Bib
    Rueckert, E.; Nakatenus, M.; Tosatto, S.; Peters, J. (2017). Learning Inverse Dynamics Models in O(n) time with LSTM networks, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
  •     Bib
    Tanneberg, D.; Peters, J.; Rueckert, E. (2017). Efficient Online Adaptation with Stochastic Recurrent Neural Networks, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
  •     Bib
    Stark, S.; Peters, J.; Rueckert, E. (2017). A Comparison of Distance Measures for Learning Nonparametric Motor Skill Libraries, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
  •     Bib
    Thiem, S.; Stark, S.; Tanneberg, D.; Peters, J.; Rueckert, E. (2017). Simulation of the underactuated Sake Robotics Gripper in V-REP, Workshop at the International Conference on Humanoid Robots (HUMANOIDS).
  •   Bib
    Grossberger, L.; Hohmann, M.R.; Peters J.; Grosse-Wentrup, M. (2017). Investigating Music Imagery as a Cognitive Paradigm for Low-Cost Brain-Computer Interfaces, Proceedings of the 7th Graz Brain-Computer Interface Conference.
  •     Bib
    Osa, T.; Peters, J.; Neumann, G. (2016). Experiments with Hierarchical Reinforcement Learning of Multiple Grasping Policies, Proceedings of the International Symposium on Experimental Robotics (ISER).
  •     Bib
    Kohlschuetter, J.; Peters, J.; Rueckert, E. (2016). Learning Probabilistic Features from EMG Data for Predicting Knee Abnormalities, Proceedings of the XIV Mediterranean Conference on Medical and Biological Engineering and Computing (MEDICON).
  •     Bib
    Modugno, V.; Neumann, G.; Rueckert, E.; Oriolo, G.; Peters, J.; Ivaldi, S. (2016). Learning soft task priorities for control of redundant robots, Proceedings of the International Conference on Robotics and Automation (ICRA).
  •   Bib
    Buechler, D.; Ott, H.; Peters, J. (2016). A Lightweight Robotic Arm with Pneumatic Muscles for Robot Learning, Proceedings of the International Conference on Robotics and Automation (ICRA).
  •     Bib
    Ewerton, M.; Maeda, G.; Neumann, G.; Kisner, V.; Kollegger, G.; Wiemeyer, J.; Peters, J. (2016). Movement Primitives with Multiple Phase Parameters, Proceedings of the International Conference on Robotics and Automation (ICRA), pp.201--206.
  •     Bib
    Vinogradska, J.; Bischoff, B.; Nguyen-Tuong, D.; Romer, A.; Schmidt, H.; Peters, J. (2016). Stability of Controllers for Gaussian Process Forward Models, Proceedings of the International Conference on Machine Learning (ICML).
  •     Bib
    Calandra, R.; Peters, J.; Rasmussen, C.E.; Deisenroth, M.P. (2016). Manifold Gaussian Processes for Regression, Proceedings of the International Joint Conference on Neural Networks (IJCNN).
  •     Bib
    Weber, P.; Rueckert, E.; Calandra, R.; Peters, J.; Beckerle, P. (2016). A Low-cost Sensor Glove with Vibrotactile Feedback and Multiple Finger Joint and Hand Motion Sensing for Human-Robot Interaction, Proceedings of the IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN).
  •     Bib
    Manschitz, S.; Gienger, M.; Kober, J.; Peters, J. (2016). Probabilistic Decomposition of Sequential Force Interaction Tasks into Movement Primitives, Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS).
  •     Bib
    van Hoof, H.; Chen, N.; Karl, M.; van der Smagt, P.; Peters, J. (2016). Stable Reinforcement Learning with Autoencoders for Tactile and Visual Data, Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS).
  •     Bib
    Yi, Z.; Calandra, R.; Veiga, F.; van Hoof, H.; Hermans, T.; Zhang, Y.; Peters, J. (2016). Active Tactile Object Exploration with Gaussian Processes, Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS).
  •   Bib
    Koc, O.; Peters, J.; Maeda, G. (2016). A New Trajectory Generation Framework in Robotic Table Tennis, Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS).
  •     Bib
    Belousov, B.; Neumann, G.; Rothkopf, C.; Peters, J. (2016). Catching Heuristics Are Optimal Control Policies, Advances in Neural Information Processing Systems (NIPS / NeurIPS).
  •     Bib
    Tanneberg, D.; Paraschos, A.; Peters, J.; Rueckert, E. (2016). Deep Spiking Networks for Model-based Planning in Humanoids, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
  •   Bib
    Huang, Y.; Buechler, D.; Koc, O.; Schoelkopf, B.; Peters, J. (2016). Jointly Learning Trajectory Generation and Hitting Point Prediction in Robot Table Tennis, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
  •     Bib
    Koert, D.; Maeda, G.J.; Lioutikov, R.; Neumann, G.; Peters, J. (2016). Demonstration Based Trajectory Optimization for Generalizable Robot Motions, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
  •   Bib
    Gomez-Gonzalez, S.; Neumann, G.; Schoelkopf, B.; Peters, J. (2016). Using Probabilistic Movement Primitives for Striking Movements, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
  •     Bib
    Ewerton, M.; Maeda, G.J.; Kollegger, G.; Wiemeyer, J.; Peters, J. (2016). Incremental Imitation Learning of Context-Dependent Motor Skills, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS), pp.351--358.
  •     Bib
    Parisi, S; Blank, A; Viernickel T; Peters, J (2016). Local-utopia Policy Selection for Multi-objective Reinforcement Learning, Proceedings of the IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning (ADPRL).
  •     Bib
    Fiebig, K.-H.; Jayaram, V.; Peters, J.; Grosse-Wentrup, M. (2016). Multi-Task Logistic Regression in Brain-Computer Interfaces, IEEE SMC 2016 — 6th Workshop on Brain-Machine Interface Systems.
  •     Bib
    van Hoof, H.; Peters, J.; Neumann, G. (2015). Learning of Non-Parametric Control Policies with High-Dimensional State Features, Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS).
  •     Bib
    Calandra, R.; Ivaldi, S.; Deisenroth, M.;Rueckert, E.; Peters, J. (2015). Learning Inverse Dynamics Models with Contacts, Proceedings of the International Conference on Robotics and Automation (ICRA).
  •     Bib
    Kroemer, O.; Daniel, C.; Neumann, G; van Hoof, H.; Peters, J. (2015). Towards Learning Hierarchical Skills for Multi-Phase Manipulation Tasks, Proceedings of the International Conference on Robotics and Automation (ICRA).
  •     Bib
    Rueckert, E.; Mundo, J.; Paraschos, A.; Peters, J.; Neumann, G. (2015). Extracting Low-Dimensional Control Variables for Movement Primitives, Proceedings of the International Conference on Robotics and Automation (ICRA).
  •     Bib
    Ewerton, M.; Neumann, G.; Lioutikov, R.; Ben Amor, H.; Peters, J.; Maeda, G. (2015). Learning Multiple Collaborative Tasks with a Mixture of Interaction Primitives, Proceedings of the International Conference on Robotics and Automation (ICRA), pp.1535--1542.
  •     Bib
    Lopes, M.; Peters, J.; Piater, J.; Toussaint, M.; Baisero, A.; Busch, B.; Erkent, O.; Kroemer, O.; Lioutikov, R.; Maeda, G.; Mollard, Y.; Munzer, T.; Shukla, D. (2015). Semi-Autonomous 3rd-Hand Robot, Workshop on Cognitive Robotics in Future Manufacturing Scenarios, European Robotics Forum, Vienna, Austria.
  •     Bib
    Paraschos, A.; Rueckert, E.; Peters, J; Neumann, G. (2015). Model-Free Probabilistic Movement Primitives for Physical Interaction, Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS).
  •       Bib
    Rueckert, E.; Lioutikov, R.; Calandra, R.; Schmidt, M.; Beckerle, P.; Peters, J. (2015). Low-cost Sensor Glove with Force Feedback for Learning from Demonstrations using Probabilistic Trajectory Representations, ICRA 2015 Workshop on Tactile and force sensing for autonomous compliant intelligent robots.
  •     Bib
    Parisi, S.; Abdulsamad, H.; Paraschos, A.; Daniel, C.; Peters, J. (2015). Reinforcement Learning vs Human Programming in Tetherball Robot Games, Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS).
  •     Bib
    Veiga, F.F.; van Hoof, H.; Peters, J.; Hermans, T. (2015). Stabilizing Novel Objects by Learning to Predict Tactile Slip, Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS).
  •     Bib
    Huang, Y.; Schoelkopf, B.; Peters, J. (2015). Learning Optimal Striking Points for A Ping-Pong Playing Robot, Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS).
  •     Bib
    Manschitz, S.; Kober, J.; Gienger, M.; Peters, J. (2015). Probabilistic Progress Prediction and Sequencing of Concurrent Movement Primitives, Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS).
  •     Bib
    Ewerton, M.; Maeda, G.J.; Peters, J.; Neumann, G. (2015). Learning Motor Skills from Partially Observed Movements Executed at Different Speeds, Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS), pp.456--463.
  •     Bib
    Wahrburg, A.; Zeiss, S.; Matthias, B.; Peters, J.; Ding, H. (2015). Combined Pose-Wrench and State Machine Representation for Modeling Robotic Assembly Skills, Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS).
  •     Bib
    Fritsche, L.; Unverzagt, F.; Peters, J.; Calandra, R. (2015). First-Person Tele-Operation of a Humanoid Robot, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
  •     Bib
    Calandra, R.; Ivaldi, S.; Deisenroth, M.; Peters, J. (2015). Learning Torque Control in Presence of Contacts using Tactile Sensing from Robot Skin, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
  •     Bib
    Maeda, G.; Neumann, G.; Ewerton, M.; Lioutikov, R.; Peters, J. (2015). A Probabilistic Framework for Semi-Autonomous Robots Based on Interaction Primitives with Phase Estimation, Proceedings of the International Symposium of Robotics Research (ISRR).
  •   Bib
    Koc, O.; Maeda, G.; Neumann, G.; Peters, J. (2015). Optimizing Robot Striking Movement Primitives with Iterative Learning Control, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
  •     Bib
    Hoelscher, J.; Peters, J.; Hermans, T. (2015). Evaluation of Interactive Object Recognition with Tactile Sensing, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
  •       Bib
    van Hoof, H.; Hermans, T.; Neumann, G.; Peters, J. (2015). Learning Robot In-Hand Manipulation with Tactile Features, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
  •     Bib
    Leischnig, S.; Luettgen, S.; Kroemer, O.; Peters, J. (2015). A Comparison of Contact Distribution Representations for Learning to Predict Object Interactions, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
  •     Bib
    Abdolmaleki, A.; Lioutikov, R.; Peters, J; Lau, N.; Reis, L.; Neumann, G. (2015). Model-Based Relative Entropy Stochastic Search, Advances in Neural Information Processing Systems (NIPS / NeurIPS), MIT Press.
  •   Bib
    Dann, C.; Neumann, G.; Peters, J. (2015). Policy Evaluation with Temporal Differences: A Survey and Comparison, Proceedings of the Twenty-Fifth International Conference on Automated Planning and Scheduling (ICAPS), pp.359-360.
  •     Bib
    Nori, F.; Peters, J.; Padois, V.; Babic, J.; Mistry, M.; Ivaldi, S. (2014). Whole-body motion in humans and humanoids, Proceedings of the Workshop on New Research Frontiers for Intelligent Autonomous Systems (NRF-IAS), pp.81-92.
  •     Bib
    Deisenroth, M.P.; Englert, P.; Peters, J.; Fox, D. (2014). Multi-Task Policy Search for Robotics, Proceedings of 2014 IEEE International Conference on Robotics and Automation (ICRA).
  •     Bib
    Bischoff, B.; Nguyen-Tuong, D.; van Hoof, H. McHutchon, A.; Rasmussen, C.E.; Knoll, A.; Peters, J.; Deisenroth, M.P. (2014). Policy Search For Learning Robot Control Using Sparse Data, Proceedings of 2014 IEEE International Conference on Robotics and Automation (ICRA).
  •     Bib
    Calandra, R.; Seyfarth, A.; Peters, J.; Deisenroth, M.P. (2014). An Experimental Comparison of Bayesian Optimization for Bipedal Locomotion, Proceedings of 2014 IEEE International Conference on Robotics and Automation (ICRA).
  •     Bib
    Kroemer, O.; van Hoof, H.; Neumann, G.; Peters, J. (2014). Learning to Predict Phases of Manipulation Tasks as Hidden States, Proceedings of 2014 IEEE International Conference on Robotics and Automation (ICRA).
  •     Bib
    Ben Amor, H.; Neumann, G.; Kamthe, S.; Kroemer, O.; Peters, J. (2014). Interaction Primitives for Human-Robot Cooperation Tasks , Proceedings of 2014 IEEE International Conference on Robotics and Automation (ICRA).
  •     Bib
    Calandra, R.; Gopalan, N.; Seyfarth, A.; Peters, J.; Deisenroth, M.P. (2014). Bayesian Gait Optimization for Bipedal Locomotion, Proceedings of the 2014 Learning and Intelligent Optimization Conference (LION8).
  •     Bib
    Kamthe, S.; Peters, J.; Deisenroth, M. (2014). Multi-modal filtering for non-linear estimation, Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP).
  •   Bib
    Manschitz, S.; Kober, J.; Gienger, M.; Peters, J. (2014). Learning to Unscrew a Light Bulb from Demonstrations, Proceedings of ISR/ROBOTIK 2014.
  •     Bib
    Lioutikov, R.; Kroemer, O.; Peters, J.; Maeda, G. (2014). Learning Manipulation by Sequencing Motor Primitives with a Two-Armed Robot, Proceedings of the 13th International Conference on Intelligent Autonomous Systems (IAS).
  •     Bib
    Daniel, C.; Viering, M.; Metz, J.; Kroemer, O.; Peters, J. (2014). Active Reward Learning, Proceedings of Robotics: Science & Systems (R:SS).
  •     Bib
    Kroemer, O.; Peters, J. (2014). Predicting Object Interactions from Contact Distributions, Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS).
  •     Bib
    Chebotar, Y.; Kroemer, O.; Peters, J. (2014). Learning Robot Tactile Sensing for Object Manipulation, Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS).
  •     Bib
    Manschitz, S.; Kober, J.; Gienger, M.; Peters, J. (2014). Learning to Sequence Movement Primitives from Demonstrations, Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS).
  •     Bib
    Luck, K.S.; Neumann, G.; Berger, E.; Peters, J.; Ben Amor, H. (2014). Latent Space Policy Search for Robotics, Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS).
  •     Bib
    Gomez, V.; Kappen, B; Peters, J.; Neumann, G (2014). Policy Search for Path Integral Control, Proceedings of the European Conference on Machine Learning (ECML).
  •     Bib
    Maeda, G.J.; Ewerton, M.; Lioutikov, R.; Amor, H.B.; Peters, J.; Neumann, G. (2014). Learning Interaction for Collaborative Tasks with Probabilistic Movement Primitives, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS), pp.527--534.
  •     Bib
    Brandl, S.; Kroemer, O.; Peters, J. (2014). Generalizing Pouring Actions Between Objects using Warped Parameters, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
  •     Bib
    Colome, A.; Neumann, G.; Peters, J.; Torras, C. (2014). Dimensionality Reduction for Probabilistic Movement Primitives, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
  •     Bib
    Rueckert, E.; Mindt, M.; Peters, J.; Neumann, G. (2014). Robust Policy Updates for Stochastic Optimal Control, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
  •     Bib
    Ivaldi, S.; Peters, J.; Padois, V.; Nori, F. (2014). Tools for simulating humanoid robot dynamics: a survey based on user feedback, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
  •     Bib
    Hermans, T.; Veiga, F.; Hoelscher, J.; van Hoof, H.; Peters, J. (2014). Demonstration: Learning for Tactile Manipulation, Advances in Neural Information Processing Systems (NIPS/NeurIPS), Demonstration Track., MIT Press.
  •     Bib
    Lioutikov, R.; Paraschos, A.; Peters, J.; Neumann, G. (2014). Sample-Based Information-Theoretic Stochastic Optimal Control, Proceedings of the International Conference on Robotics and Automation (ICRA).
  •       Bib
    Daniel, C.; Neumann, G.; Kroemer, O.; Peters, J. (2013). Learning Sequential Motor Tasks, Proceedings of 2013 IEEE International Conference on Robotics and Automation (ICRA).
  •       Bib
    Englert, P.; Paraschos, A.; Peters, J.; Deisenroth, M. P. (2013). Model-based Imitation Learning by Probabilistic Trajectory Matching, Proceedings of 2013 IEEE International Conference on Robotics and Automation (ICRA).
  •       Bib
    Gopalan, N.; Deisenroth, M. P.; Peters, J. (2013). Feedback Error Learning for Rhythmic Motor Primitives, Proceedings of 2013 IEEE International Conference on Robotics and Automation (ICRA).
  •       Bib
    Peters, J.; Kober, J.; Muelling, K.; Kroemer, O.; Neumann, G. (2013). Towards Robot Skill Learning: From Simple Skills to Table Tennis, Proceedings of the European Conference on Machine Learning (ECML), Nectar Track.
  •       Bib
    Kupcsik, A.G.; Deisenroth, M.P.; Peters, J.; Neumann, G. (2013). Data-Efficient Generalization of Robot Skills with Contextual Policy Search, Proceedings of the National Conference on Artificial Intelligence (AAAI) .
  •       Bib
    Bocsi, B.; Csato, L.; Peters, J. (2013). Alignment-based Transfer Learning for Robot Models, Proceedings of the 2013 International Joint Conference on Neural Networks (IJCNN) .
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    Daniel, C.; Neumann, G.; Peters, J. (2013). Autonomous Reinforcement Learning with Hierarchical REPS, Proceedings of the 2013 International Joint Conference on Neural Networks (IJCNN) .
  •   Bib
    Peters, J.; Kober, J.; Muelling, K.; Nguyen-Tuong, D.; Kroemer, O. (2013). Learning Skills with Motor Primitives, Proceedings of the 16th Yale Learning Workshop.
  •   Bib
    Neumann, G.; Kupcsik, A.G.; Deisenroth, M.P.; Peters, J. (2013). Information-Theoretic Motor Skill Learning, Proceedings of the AAAI 2013 Workshop on Intelligent Robotic Systems.
  •     Bib
    Ben Amor, H.; Vogt, D.; Ewerton, M.; Berger, E.; Jung, B.; Peters, J. (2013). Learning Responsive Robot Behavior by Imitation, Proceedings of the 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
  •     Bib
    van Hoof, H.; Kroemer, O; Peters, J. (2013). Probabilistic Interactive Segmentation for Anthropomorphic Robots in Cluttered Environments , Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
  •     Bib
    Paraschos, A.; Neumann, G; Peters, J. (2013). A Probabilistic Approach to Robot Trajectory Generation, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
  •     Bib
    Paraschos, A.; Daniel, C.; Peters, J.; Neumann, G (2013). Probabilistic Movement Primitives, Advances in Neural Information Processing Systems (NIPS / NeurIPS), MIT Press.
  •       Bib
    Daniel, C.; Neumann, G.; Peters, J. (2012). Hierarchical Relative Entropy Policy Search, Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS 2012).
  •       Bib
    Kroemer, O.; Ugur, E.; Oztop, E. ; Peters, J. (2012). A Kernel-based Approach to Direct Action Perception, Proceedings of the International Conference on Robotics and Automation (ICRA).
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    Bocsi, B.; Hennig, P.; Csato, L.; Peters, J. (2012). Learning Tracking Control with Forward Models, Proceedings of the International Conference on Robotics and Automation (ICRA).
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    Wang, Z.;Deisenroth, M; Ben Amor, H.; Vogt, D.; Schoelkopf, B.; Peters, J. (2012). Probabilistic Modeling of Human Movements for Intention Inference, Proceedings of Robotics: Science and Systems (R:SS).
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    Peters, J.; Kober, J.; Muelling, K.; Nguyen-Tuong, D.; Kroemer, O. (2012). Robot Skill Learning, Proceedings of the European Conference on Artificial Intelligence (ECAI).
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    Boularias, A.; Kroemer, O.; Peters, J. (2012). Structured Apprenticeship Learning, Proceedings of the European Conference on Machine Learning (ECML).
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    Meyer, T.; Peters, J.;Broetz, D.; Zander, T.; Schoelkopf, B.; Soekadar, S.; Grosse-Wentrup, M. (2012). A Brain-Robot Interface for Studying Motor Learning after Stroke, Proceedings of the International Conference on Robot Systems (IROS).
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    Deisenroth, M.P.; Calandra, R.; Seyfarth, A.; Peters, J. (2012). Toward Fast Policy Search for Learning Legged Locomotion, Proceedings of the International Conference on Robot Systems (IROS).
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    van Hoof, H.; Kroemer, O.;Ben Amor, H.; Peters, J. (2012). Maximally Informative Interaction Learning for Scene Exploration, Proceedings of the International Conference on Robot Systems (IROS).
  •       Bib
    Daniel, C.; Neumann, G.; Peters, J. (2012). Learning Concurrent Motor Skills in Versatile Solution Spaces, Proceedings of the International Conference on Robot Systems (IROS).
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    Ben Amor, H.; Kroemer, O.; Hillenbrand, U.; Neumann, G.; Peters, J. (2012). Generalization of Human Grasping for Multi-Fingered Robot Hands, Proceedings of the International Conference on Robot Systems (IROS).
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    Kober, J; Muelling, K.; Peters, J. (2012). Learning Throwing and Catching Skills, Proceedings of the International Conference on Robot Systems (IROS), Video Track.
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    Deisenroth, M.P.; Peters, J. (2012). Solving Nonlinear Continuous State-Action-Observation POMDPs for Mechanical Systems with Gaussian Noise, Proceedings of the European Workshop on Reinforcement Learning (EWRL).
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    Muelling, K.; Kober, J.; Kroemer, O.; Peters, J. (2012). Learning to Select and Generalize Striking Movements in Robot Table Tennis, Proceedings of the AAAI 2012 Fall Symposium on Robots that Learn Interactively from Human Teachers.
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    Meyer, T.; Peters, J.; Broetz, D.; Zander, T.; Schoelkopf, B.; Soekadar, S.; Grosse-Wentrup, M. (2012). Investigating the Neural Basis for Stroke Rehabilitation by Brain-Computer Interfaces, International Conference on Neurorehabilitation.
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    Kroemer, O.; Ben Amor, H.; Ewerton, M.; Peters, J. (2012). Point Cloud Completion Using Extrusions, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
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    Boularias, A.; Kroemer, O.; Peters, J. (2012). Algorithms for Learning Markov Field Policies, Advances in Neural Information Processing Systems 26 (NIPS/NeurIPS), Cambridge, MA: MIT Press., MIT Press.
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    Lampariello, R.; Nguyen Tuong, D.; Castellini, C.; Hirzinger, G.; Peters, J. (2011). Energy-optimal robot catching in real-time, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA).
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    Kroemer, O.; Peters, J. (2011). A Flexible Hybrid Framework for Modeling Complex Manipulation Tasks, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA).
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    Kroemer, O.; Peters, J. (2011). Active Exploration for Robot Parameter Selection in Episodic Reinforcement Learning, Proceedings of the 2011 IEEE International Symposium on Approximate Dynamic Programming and Reinforcement Learning (ADPRL).
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    Boularias, A.; Kroemer, O.; Peters, J. (2011). Learning Robot Grasping from 3D Images with Markov Random Fields, IEEE/RSJ International Conference on Intelligent Robot Systems (IROS).
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    Kroemer, O.; Peters, J. (2011). A Non-Parametric Approach to Dynamic Programming, Advances in Neural Information Processing Systems 25 (NIPS/NeurIPS), MIT Press.
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    Bocsi, B.; Nguyen-Tuong, D; Csato, L; Schoelkopf, B.; Peters, J. (2011). Learning Inverse Kinematics with Structured Prediction, IEEE/RSJ International Conference on Intelligent Robot Systems (IROS).
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    Wang, Z.; Lampert, C; Muelling, K; Schoelkopf, B.; Peters, J. (2011). Learning Anticipation Policies for Robot Table Tennis, IEEE/RSJ International Conference on Intelligent Robot Systems (IROS).
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    Nguyen Tuong, D.; Peters, J. (2011). Learning Task-Space Tracking Control with Kernels, IEEE/RSJ International Conference on Intelligent Robot Systems (IROS).
  •       Bib
    Kober, J.; Peters, J. (2011). Learning Elementary Movements Jointly with a Higher Level Task, IEEE/RSJ International Conference on Intelligent Robot Systems (IROS).
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    Gomez Rodriguez, M.; Grosse-Wentrup, M.; Hill, J.; Schoelkopf, B.; Gharabaghi, A.; Peters, J. (2011). Towards Brain-Robot Interfaces for Stroke Rehabilitation, Proceedings of the International Conference on Rehabilitation Robotics (ICORR).
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    Wang, Z.; Boularias, A.; Muelling, K.; Peters, J. (2011). Balancing Safety and Exploitability in Opponent Modeling, Proceedings of the Twenty-Fifth National Conference on Artificial Intelligence (AAAI).
  •     Bib
    Kober, J.; Oztop, E.; Peters, J. (2011). Reinforcement Learning to adjust Robot Movements to New Situations, Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), Best Paper Track.
  •     Bib
    Boularias, A.; Kober, J.; Peters, J. (2011). Relative Entropy Inverse Reinforcement Learning, Proceedings of Fourteenth International Conference on Artificial Intelligence and Statistics (AISTATS 2011).
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    Kober, J.; Oztop, E.; Peters, J. (2010). Reinforcement Learning to adjust Robot Movements to New Situations, Proceedings of Robotics: Science and Systems (R:SS).
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    Kroemer, O.; Detry, R.; Piater, J.; Peters, J. (2010). Adapting Preshaped Grasping Movements using Vision Descriptors, From Animals to Animats 11, International Conference on the Simulation of Adaptive Behavior (SAB).
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    Kroemer, O.; Detry, R.; Piater, J.; Peters, J. (2010). Grasping with Vision Descriptors and Motor Primitives, Proceedings of the International Conference on Informatics in Control, Automation and Robotics (ICINCO).
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    Muelling, K.; Kober, J.; Peters, J. (2010). Simulating Human Table Tennis with a Biomimetic Robot Setup, From Animals to Animats 11, International Conference on the Simulation of Adaptive Behavior (SAB).
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    Nguyen Tuong, D.; Peters, J. (2010). Incremental Sparsification for Real-time Online Model Learning, Proceedings of Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS 2010).
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    Peters, J.; Muelling, K.; Altun, Y. (2010). Relative Entropy Policy Search, Proceedings of the Twenty-Fourth National Conference on Artificial Intelligence (AAAI), Physically Grounded AI Track.
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    Kober, J.; Muelling, K.; Kroemer, O.; Lampert, C.H.; Schoelkopf, B.; Peters, J. (2010). Movement Templates for Learning of Hitting and Batting, IEEE International Conference on Robotics and Automation (ICRA).
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    Nguyen Tuong, D.; Peters, J. (2010). Using Model Knowledge for Learning Inverse Dynamics, IEEE International Conference on Robotics and Automation.
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    Erkan, A.: Kroemer, O.; Detry, R.; Altun, Y.; Piater, J.; Peters, J. (2010). Learning Probabilistic Discriminative Models of Grasp Affordances under Limited Supervision, Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
  •       Bib
    Muelling, K.; Kober, J.; Peters, J. (2010). A Biomimetic Approach to Robot Table Tennis, Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
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    Gomez Rodriguez, M.; Grosse Wentrup, M.; Peters, J.; Naros, G.; Hill, J.; Gharabaghi, A.; Schoelkopf, B. (2010). Epidural ECoG Online Decoding of Arm Movement Intention in Hemiparesis, 1st ICPR Workshop on Brain Decoding: Pattern Recognition Challenges in Neuroimaging.
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    Gomez Rodriguez, M.; Peters, J.; Hill, J.; Schoelkopf, B.; Gharabaghi, A.; Grosse-Wentrup, M. (2010). Closing the Sensorimotor Loop: Haptic Feedback Facilitates Decoding of Arm Movement Imagery, Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics (Workshop on Brain-Machine Interfaces).
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    Gomez Rodriguez, M.; Peters, J.; Hill, J.; Gharabaghi, A.; Schoelkopf, B.; Grosse-Wentrup, M. (2010). BCI and robotics framework for stroke rehabilitation, Proceedings of the 4th International BCI Meeting, May 31 - June 4, 2010. Asilomar, CA, USA.
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    Chiappa, S.; Peters, J. (2010). Movement extraction by detecting dynamics switches and repetitions, Advances in Neural Information Processing Systems 24 (NIPS/NeurIPS), Cambridge, MA: MIT Press.
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    Alvaro, M.; Peters, J.; Schoelfkopf, B.; Lawrence, N. (2010). Switched Latent Force Models for Movement Segmentation, Advances in Neural Information Processing Systems 24 (NIPS/NeurIPS), Cambridge, MA: MIT Press.
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    Muelling, K.; Kober, J.; Peters, J. (2010). Learning Table Tennis with a Mixture of Motor Primitives, 10th IEEE-RAS International Conference on Humanoid Robots (Humanoids 2010).
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    Peters, J.; Muelling, K.; Kober, J. (2010). Experiments with Motor Primitives to learn Table Tennis, 12th International Symposium on Experimental Robotics (ISER 2010).
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    Hachiya, H.; Peters, J.; Sugiyama, M. (2009). Efficient Sample Reuse in EM-based Policy Search, Proceedings of the 16th European Conference on Machine Learning (ECML 2009).
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    Peters, J.; Kober, J.; Muelling, K.; Nguyen-Tuong, D.; Kroemer, O. (2009). Towards Motor Skill Learning for Robotics, Proceedings of the International Symposium on Robotics Research (ISRR), Invited Paper.
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    Nguyen Tuong, D.; Seeger, M.; Peters, J. (2009). Local Gaussian Process Regression for Real Time Online Model Learning and Control, Advances in Neural Information Processing Systems 22 (NIPS/NeurIPS), Cambridge, MA: MIT Press.
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    Neumann, G.; Peters, J. (2009). Fitted Q-iteration by Advantage Weighted Regression, Advances in Neural Information Processing Systems 22 (NIPS/NeurIPS), Cambridge, MA: MIT Press.
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    Kober, J.; Peters, J. (2009). Policy Search for Motor Primitives in Robotics, Advances in Neural Information Processing Systems 22 (NIPS/NeurIPS), Cambridge, MA: MIT Press.
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    Chiappa, S.; Kober, J.; Peters, J. (2009). Using Bayesian Dynamical Systems for Motion Template Libraries, Advances in Neural Information Processing Systems 22 (NIPS/NeurIPS), Cambridge, MA: MIT Press.
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    Hoffman, M.; de Freitas, N. ; Doucet, A.; Peters, J. (2009). An Expectation Maximization Algorithm for Continuous Markov Decision Processes with Arbitrary Reward, Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics (AIStats).
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    Peters, J.; Kober, J. (2009). Using Reward-Weighted Imitation for Robot Reinforcement Learning, Proceedings of the 2009 IEEE International Symposium on Approximate Dynamic Programming and Reinforcement Learning.
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    Hachiya, H.; Akiyama, T.; Sugiyama, M.; Peters, J. (2009). Efficient Data Reuse in Value Function Approximation, Proceedings of the 2009 IEEE International Symposium on Approximate Dynamic Programming and Reinforcement Learning.
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    Kober, J.; Peters, J. (2009). Learning Motor Primitives for Robotics, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA).
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    Piater, J.; Jodogne, S.; Detry, R.; Kraft, D.; Krueger, N.; Kroemer, O.; Peters, J. (2009). Learning Visual Representations for Interactive Systems, Proceedings of the International Symposium on Robotics Research (ISRR), Invited Paper.
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    Kober, J.; Peters, J. (2009). Learning new basic Movements for Robotics, Proceedings of Autonome Mobile Systeme (AMS 2009).
  •     Bib
    Muelling, K.; Peters, J. (2009). A computational model of human table tennis for robot application, Proceedings of Autonome Mobile Systeme (AMS 2009).
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    Kroemer, O.; Detry, R.; Piater, J.; Peters, J. (2009). Active Learning Using Mean Shift Optimization for Robot Grasping, Proceedings of the 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2009).
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    Nguyen Tuong, D.; Seeger, M.; Peters, J. (2009). Sparse Online Model Learning for Robot Control with Support Vector Regression, Proceedings of the 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2009).
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    Sigaud, O.; Peters, J. (2009). From Motor Learning to Interaction Learning in Robots, Proceedings of Journees Nationales de la Recherche en Robotique.
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    Neumann, G.; Maass, W; Peters, J. (2009). Learning Complex Motions by Sequencing Simpler Motion Templates, Proceedings of the International Conference on Machine Learning (ICML2009).
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    Detry, R; Baseski, E.; Popovic, M.; Touati, Y.; Krueger, N; Kroemer, O.; Peters, J.; Piater, J; (2009). Learning Object-specific Grasp Affordance Densities, Proceedings of the International Conference on Development & Learning (ICDL 2009).
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    Lampert, C.H.; Peters, J. (2009). Active Structured Learning for High-Speed Object Detection, Proceedings of the DAGM (Pattern Recognition).
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    Deisenroth, M.P.; Peters, J.; Rasmussen, C.E. (2008). Approximate Dynamic Programming with Gaussian Processes, American Control Conference.
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    Peters, J.; Seeger, M. (2008). Computed Torque Control with Nonparametric Regressions Techniques, American Control Conference.
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    Deisenroth, M.P.; Rasmussen, C.E.; Peters, J. (2008). Model-Based Reinforcement Learning with Continuous States and Actions, Proceedings of the European Symposium on Artificial Neural Networks (ESANN 2008), pp.19-24.
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    Nguyen Tuong, D.; Peters, J. (2008). Learning Inverse Dynamics: a Comparison, Proceedings of the European Symposium on Artificial Neural Networks (ESANN 2008).
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    Peters, J.; Nguyen-Tuong, D. (2008). Real-Time Learning of Resolved Velocity Control on a Mitsubishi PA-10, International Conference on Robotics and Automation (ICRA).
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    Hachiya, H.; Akiyama, T.; Sugiyama, M.; Peters, J. (2008). Adaptive Importance Sampling with Automatic Model Selection in Value Function Approximation, Proceedings of the Twenty-Third National Conference on Artificial Intelligence (AAAI 2008).
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    Wierstra, D.; Schaul, T.; Peters, J.; Schmidhuber, J. (2008). Natural Evolution Strategies, 2008 IEEE Congress on Evolutionary Computation.
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    Nguyen Tuong, D.; Peters, J. (2008). Local Gaussian Processes Regression for Real-time Model-based Robot Control, International Conference on Intelligent Robot Systems (IROS).
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    Kober, J.; Mohler, B.; Peters, J. (2008). Learning Perceptual Coupling for Motor Primitives, International Conference on Intelligent Robot Systems (IROS).
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    Wierstra, D.; Schaul, T.; Peters, J.; Schmidthuber, J. (2008). Fitness Expectation Maximization, 10th International Conference on Parallel Problem Solving from Nature (PPSN 2008).
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    Wierstra, D.; Schaul,T.; Peters, J.; Schmidhuber, J. (2008). Episodic Reinforcement Learning by Logistic Reward-Weighted Regression, Proceedings of the International Conference on Artificial Neural Networks (ICANN).
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    Sehnke, F.; Osendorfer, C; Rueckstiess, T; Graves, A.; Peters, J.; Schmidhuber, J. (2008). Policy Gradients with Parameter-based Exploration for Control, Proceedings of the International Conference on Artificial Neural Networks (ICANN).
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    Peters, J.; Kober, J.; Nguyen-Tuong, D. (2008). Policy Learning - a unified perspective with applications in robotics, Proceedings of the European Workshop on Reinforcement Learning (EWRL).
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    Kober, J.; Peters, J. (2008). Reinforcement Learning of Perceptual Coupling for Motor Primitives, Proceedings of the European Workshop on Reinforcement Learning (EWRL).
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    Nguyen Tuong, D.; Peters, J.; Seeger, M.; Schoelkopf, B. (2008). Learning Robot Dynamics for Computed Torque Control using Local Gaussian Processes Regression, Proceedings of the ECSIS Symposium on Learning and Adaptive Behavior in Robotic Systems, LAB-RS 2008.
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    Peters, J.; Schaal, S. (2007). Policy Learning for Motor Skills, Proceedings of 14th International Conference on Neural Information Processing (ICONIP).
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    Wierstra, D.; Foerster, A.; Peters, J.; Schmidhuber, J. (2007). Solving Deep Memory POMDPs with Recurrent Policy Gradients, Proceedings of the International Conference on Artificial Neural Networks (ICANN).
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    Peters, J.; Schaal, S.; Schoelkopf, B. (2007). Towards Machine Learning of Motor Skills, Proceedings of Autonome Mobile Systeme (AMS).
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    Theodorou, E; Peters, J.; Schaal, S. (2007). Reinforcement Learning for Optimal Control of Arm Movements, Abstracts of the 37st Meeting of the Society of Neuroscience.
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    Peters, J.; Schaal, S. (2007). Reinforcement learning for operational space control, International Conference on Robotics and Automation (ICRA2007).
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    Peters, J.;Schaal, S. (2007). Using reward-weighted regression for reinforcement learning of task space control, Proceedings of the 2007 IEEE International Symposium on Approximate Dynamic Programming and Reinforcement Learning.
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    Peters, J.; Schaal, S. (2007). Applying the episodic natural actor-critic architecture to motor primitive learning, Proceedings of the 2007 European Symposium on Artificial Neural Networks (ESANN).
  •     Bib
    Peters, J.;Schaal, S. (2007). Reinforcement learning by reward-weighted regression for operational space control, Proceedings of the International Conference on Machine Learning (ICML2007).
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    Peters, J.;Theodorou, E.;Schaal, S. (2007). Policy gradient methods for machine learning, INFORMS Conference of the Applied Probability Society.
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    Riedmiller, M.;Peters, J.;Schaal, S. (2007). Evaluation of policy gradient methods and variants on the cart-pole benchmark, Proceedings of the 2007 IEEE International Symposium on Approximate Dynamic Programming and Reinforcement Learning.
  •     Bib
    Peters, J.;Schaal, S. (2006). Learning operational space control, Robotics: Science and Systems (RSS 2006), Cambridge, MA: MIT Press.
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    Peters, J.;Schaal, S. (2006). Reinforcement Learning for Parameterized Motor Primitives, Proceedings of the 2006 International Joint Conference on Neural Networks (IJCNN).
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    Ting, J.;Mistry, M.;Nakanishi, J.;Peters, J.;Schaal, S. (2006). A Bayesian approach to nonlinear parameter identification for rigid body dynamics, Robotics: Science and Systems (RSS 2006), Cambridge, MA: MIT Press.
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    Peters, J.;Schaal, S. (2006). Policy gradient methods for robotics, Proceedings of the IEEE International Conference on Intelligent Robotics Systems (IROS 2006).
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    Nakanishi, J.;Cory, R.;Mistry, M.;Peters, J.;Schaal, S. (2005). Comparative experiments on task space control with redundancy resolution, IEEE International Conference on Intelligent Robots and Systems (IROS 2005).
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    Peters, J.;Vijayakumar, S.;Schaal, S. (2005). Natural Actor-Critic, Proceedings of the 16th European Conference on Machine Learning (ECML 2005).
  •     Bib
    Peters, J.;Mistry, M.;Udwadia, F. E.;Schaal, S. (2005). A new methodology for robot control design, The 5th ASME International Conference on Multibody Systems, Nonlinear Dynamics, and Control (MSNDC 2005).
  •     Bib
    Peters, J.;Mistry, M.;Udwadia, F. E.;Cory, R.;Nakanishi, J.;Schaal, S. (2005). A unifying framework for the control of robotics systems, IEEE International Conference on Intelligent Robots and Systems (IROS 2005).
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    Schaal, S.;Peters, J.;Nakanishi, J.;Ijspeert, A. (2004). Learning Movement Primitives, International Symposium on Robotics Research (ISRR2003).
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    Peters, J.; Schaal, S. (2004). Learning Motor Primitives with Reinforcement Learning, Proceedings of the 11th Joint Symposium on Neural Computation.
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    Mohajerian, P.;Peters, J.;Ijspeert, A.;Schaal, S. (2003). A unifying computational framework for optimization and dynamic systems approaches to motor control, Proceedings of the 10th Joint Symposium on Neural Computation (JSNC 2003).
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    Peters, J.;Vijayakumar, S.;Schaal, S. (2003). Reinforcement learning for humanoid robotics, IEEE-RAS International Conference on Humanoid Robots (Humanoids2003).
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    Peters, J.;Vijayakumar, S.;Schaal, S. (2003). Scaling reinforcement learning paradigms for motor learning, Proceedings of the 10th Joint Symposium on Neural Computation (JSNC 2003).
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    Schaal, S.;Peters, J.;Nakanishi, J.;Ijspeert, A. (2003). Control, planning, learning, and imitation with dynamic movement primitives, Workshop on Bilateral Paradigms on Humans and Humanoids, IEEE International Conference on Intelligent Robots and Systems (IROS 2003).
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    Vijayakumar, S.; D’Souza, A.; Peters, J.; Conradt, J.; Rutkowski,T.; Ijspeert, A.; Nakanishi, J.; Inoue, M.; Shibata, T.; Wiryo, A.; Itti, L.; Amari, S.; Schaal, S (2002). Real-Time Statistical Learning for Oculomotor Control and Visuomotor Coordination, Advances in Neural Information Processing Systems (NIPS/NeurIPS), Demonstration Track.
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    Burdet, E.; Tee, K.P.; Chew, C.M.; Peters, J.; Bt, V.L. (2001). Hybrid IDM/Impedance Learning in Human Movements, First International Symposium on Measurement, Analysis and Modeling of Human Functions Proceedings.
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    Peters, J.; Riener, R (2000). A real-time model of the human knee for application in virtual orthopaedic trainer, Proceedings of the 10th International Conference on Biomedical Engineering Conference (ICBME).