- Gebhardt, G.H.W.; Daun, K.; Schnaubelt, M.; Neumann, G. (submitted). Learning Policies for Object Manipulation with Robot Swarms, Submitted to Advanced Robotics (ARJ).
- Gebhardt, G.H.W.; Hüttenrauch, M.; Neumann, G. (submitted). Using M-Embeddings to Learn Control Strategies for Robot Swarms, Submitted to Swarm Intelligence.
- Gebhardt, G.H.W.; Kupcsik, A.; Neumann, G. (2019). The Kernel Kalman Rule, Machine Learning Journal (MLJ), 108, 12, pp.2113–2157, Springer US.
- Gebhardt, G.H.W. (2019). Using Mean Embeddings for State Estimation and Reinforcement Learning, PhD Thesis.
- Gebhardt, G.H.W.; Daun, K.; Schnaubelt, M.; Neumann, G. (2018). Learning Robust Policies for Object Manipulation with Robot Swarms, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA).
- Gebhardt, G.H.W.; Kupcsik, A.G.; Neumann, G. (2017). The Kernel Kalman Rule - Efficient Nonparametric Inference with Recursive Least Squares, Proceedings of the National Conference on Artificial Intelligence (AAAI).
- Gebhardt, G.H.W.; Daun, K.; Schnaubelt, M.; Hendrich, A.; Kauth, D.; Neumann, G. (2017). Learning to Assemble Objects with a Robot Swarm, Proceedings of the International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS), pp.1547--1549, International Foundation for Autonomous Agents and Multiagent Systems.
- Gebhardt, G.H.W.; Kupcsik, A.; Neumann, G. (2015). Learning Subspace Conditional Embedding Operators, Large-Scale Kernel Learning Workshop at ICML 2015.
- Gebhardt, G.H.W. (2014). Embedding Kalman Filters into Reproducing Kernel Hilbert Spaces, Master Thesis.
- Amend, S.; Gebhardt, G.H.W. (2013). Learning to Serve and Bounce a Ball, Proceedings of Projektpraktikum Robot Learning.
|
