Conferences and Journals
Pajarinen, J.; Arenz, O.; Peters, J.; Neumann, N. (in press). Probabilistic approach to physical object disentangling, IEEE Robotics and Automation Letters (RA-L).   BibTeX Reference [BibTex]

Arenz, O.; Zhong, M.; Neumann G. (2020). Trust-Region Variational Inference with Gaussian Mixture Models, Journal of Machine Learning Research (JMLR).   Download Article [PDF]   BibTeX Reference [BibTex]

Ewerton, M.; Arenz, O.; Peters, J. (2020). Assisted Teleoperation in Changing Environments with a Mixture of Virtual Guides, Advanced Robotics, 34.   BibTeX Reference [BibTex]

Becker, P.; Arenz, O.; Neumann, G. (2020). Expected Information Maximization: Using the I-Projection for Mixture Density Estimation, International Conference on Learning Representations (ICLR).   Download Article [PDF]   BibTeX Reference [BibTex]

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).   Download Article [PDF]   BibTeX Reference [BibTex]

Abi Farraj, F.; Pacchierotti, C.; Arenz, O.; Neumann, G.; Giordano, P. (2019). A Haptic Shared-Control Architecture for Guided Multi-Target Robotic Grasping, IEEE Transactions on Haptics.   Download Article [PDF]   BibTeX Reference [BibTex]

Ewerton, M.; Arenz, O.; Maeda, G.; Koert, D.; Kolev, Z.; Takahashi, M.; Peters, J. (2019). Learning Trajectory Distributions for Assisted Teleoperation and Path Planning, Frontiers in Robotics and AI.   Download Article [PDF]   BibTeX Reference [BibTex]

Arenz, O.; Zhong, M.; Neumann, G. (2018). Efficient Gradient-Free Variational Inference using Policy Search, in: Dy, Jennifer and Krause, Andreas (eds.), Proceedings of the International Conference on Machine Learning (ICML), 80, pp.234--243, PMLR.   Download Article [PDF]   BibTeX Reference [BibTex]

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).   Download Article [PDF]   BibTeX Reference [BibTex]

Arenz, O.; Abdulsamad, H.; Neumann, G. (2016). Optimal Control and Inverse Optimal Control by Distribution Matching, Proceedings of the International Conference on Intelligent Robots and Systems (IROS), IEEE.   Download Article [PDF]   BibTeX Reference [BibTex]
Preprints
Arenz, O.; Neumann, G. (2020). Non-Adversarial Imitation Learning and its Connections to Adversarial Methods, arXiv.   Download Article [PDF]   BibTeX Reference [BibTex]
Workshops
Abi-Farraj, F.; Pacchierotti, C.; Arenz, O.; Neumann, G.; Giordano, P. (2020). Haptic-based Guided Grasping in a Cluttered Environment, IEEE Haptics Symposium.   Download Article [PDF]   BibTeX Reference [BibTex]

Arenz, O.; Neumann G. (2019). Non-Adversarial Inverse Reinforcement Learning by Distribution Matching, Bosch AICON 2019.   Download Article [PDF]   BibTeX Reference [BibTex]

Arenz, O.; Neumann G. (2019). Inverse Reinforcement Learning from Observation using the I-Projection, Amazon Research Days 2019 (Berlin).   BibTeX Reference [BibTex]

Pinsler, R.; Maag, M.; Arenz, O.; Neumann, G. (2018). Inverse Reinforcement Learning of Bird Flocking Behavior, Swarms: From Biology to Robotics and Back (ICRA Workshop).   Download Article [PDF]   BibTeX Reference [BibTex]

Arenz, O.; Neumann, G. (2016). Iterative Cost Learning from Different Types of Human Feedback, IROS 2016 Workshop on Human-Robot Collaboration.   Download Article [PDF]   BibTeX Reference [BibTex]

Arenz, O.; Abdulsamad, H.; Neumann, G. (2016). (Inverse) Optimal Control for Matching Higher-Order Moments, DGR Days (Leipzig).   Download Article [PDF]   BibTeX Reference [BibTex]
Theses

Arenz, O. (2021). Sample-Efficient I-Projections for Robot Learning, Ph.D. Thesis, TU Darmstadt.   Download Article [PDF]   BibTeX Reference [BibTex]

Arenz, O. (2014). Feature Extraction for Inverse Reinforcement Learning, Master Thesis.   Download Article [PDF]   BibTeX Reference [BibTex]

Arenz, O. (2012). Monte-Carlo Chess.   Download Article [PDF]   BibTeX Reference [BibTex]

  

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