Gregor Gebhardt Team
I have graduated and moved to the Biorobotics lab of Prof. Dr. Tim Landgraf at Free University Berlin as postdoc. You can still reach me via gregor@robot-learning.de. See my new FU Berlin homepage.
Gregor Gebhardt
Quick Info
Research Interests
Machine Learning, Robotics, Imitation Learning, Reinforcement Learning, Human-Robot Interaction
More Information
Contact Information
gregor.gebhardt@fu-berlin.de
Gregor joined the Intelligent Autonomous System (IAS) lab as a PhD student in January, 2015. During his PhD studies he was working on non-parametric methods for filtering, prediction and smoothing of time series as well as on non-parametric and deep representations of large sets of homogeneous observations for (deep) reinforcement learning.Gregor started his studies in computer science at the Freie Universität Berlin, where he completed his Bachelor's degree with a thesis written under the supervision of Prof. Dr. Marc Toussaint and Dr. Tobias Lang. For his Master's studies he moved on to the Technische Universität Darmstadt, where the specialized Master's program "Autonomous Systems" gave him the opportunity to focus on the most interesting fields of computer science: machine learning, robotics, computer vision and control theory. He completed his Master's degree by a thesis entitled “Embedding Kalman Filters into Reproducing Kernel Hilbert Spaces", supervised by Prof. Dr. Gerhard Neumann and Prof. Dr. Jan Peters.
Research Interests
Machine Learning, Robotics, (Deep) Reinforcement Learning, Swarm Robotics
Key References
- Gebhardt, G.H.W.; Kupcsik, A.; Neumann, G. (2019). The Kernel Kalman Rule, Machine Learning Journal (MLJ), 108, 12, pp.2113–2157, Springer US. Download Article BibTeX Reference
- Gebhardt, G.H.W.; Daun, K.; Schnaubelt, M.; Neumann, G. (submitted). Learning Policies for Object Manipulation with Robot Swarms, Submitted to Advanced Robotics (ARJ). Download Article BibTeX Reference
- Gebhardt, G.H.W.; Hüttenrauch, M.; Neumann, G. (submitted). Using M-Embeddings to Learn Control Strategies for Robot Swarms, Submitted to Swarm Intelligence. Download Article BibTeX Reference
- 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). Download Article BibTeX Reference
- Gebhardt, G.H.W.; Kupcsik, A.; Neumann, G. (2015). Learning Subspace Conditional Embedding Operators, Large-Scale Kernel Learning Workshop at ICML 2015. Download Article BibTeX Reference
