Combining Reconstruction and Contrastive Methods for Multimodal Representations in RL
Philipp Becker, Sebastian Mossburger, Fabian Otto, Gerhard Neumann
Published in Reinforcment Learning Conference (RLC), 2024
Paper | Code | Project Page
Publications
You can also find my articles on my Google Scholar profile.
Key Publications
On Uncertainty in Deep State Space Models for Model-Based Reinforcement Learning
Philipp Becker, Gerhard Neumann
Published in Transactions on Machine Learning Research (TMLR), 2022
Differentiable Trust Region Layers for Deep Reinforcement Learning
Fabian Otto, Philipp Becker, Ngo Anh Vien, Hanna Carolin Ziesche, Gerhard Neumann
Published in International Conference on Learning Representations (ICLR), 2021
Expected Information Maximization: Using the I-Projection for Mixture Density Estimation
Philipp Becker, Oleg Arenz, Gerhard Neumann
Published in International Conference on Learning Representations (ICLR), 2020
Recurrent Kalman Networks: Factorized Inference in High-Dimensional Deep Feature Spaces
Philipp Becker, Harit Pandya, Gregor Gebhardt, Cheng Zhao, James Taylor, Gerhard Neumann
Published in International Conference on Machine Learning (ICML), 2019
All Publications
PointPatchRL-Masked Reconstruction Improves Reinforcement Learning on Point Clouds
Balazs Gyenes, Nikolai Franke, Philipp Becker, Gerhard Neumann
Published in Conference on Robot Learning (CoRL), 2024
MuTT: A Multimodal Trajectory Transformer for Robot Skills
Claudius Kienle, Benjamin Alt, Onur Celik, Philipp Becker, Darko Katic, Rainer Jakel, Gerhard Neumann
Published in International Conference on Intelligent Robots and Systems (IROS), 2024
KalMamba: Towards Efficient Probabilistic State Space Models for RL under Uncertainty
Philipp Becker, Niklas Freymuth, Gerhard Neumann
Published in Aligning Reinforcement Learning Experimentalists and Theorists Workshop @ ICML; Next Generation of Sequence Modeling Architectures Workshop @ ICML; Training Agents with Foundation Models @ RLC, 2024
Iterative Sizing Field Prediction for Adaptive Mesh Generation From Expert Demonstrations
Niklas Freymuth, Philipp Dahlinger, Tobias Würth, Philipp Becker, Aleksandar Taranovic, Onno Grönheim, Luise Kärger, Gerhard Neumann
Published in AI for Science Workshop @ ICML, 2024
Beyond Deep Ensembles: A Large-Scale Evaluation of Bayesian Deep Learning under Distribution Shift
Florian Seligmann, Philipp Becker, Michael Volpp, Gerhard Neumann
Published in Advances in Neural Information Processing Systems (NeurIPS), 2023
Information-Theoretic Trust Regions for Stochastic Gradient-Based Optimization
Philipp Dahlinger, Philipp Becker, Maximilian Hüttenrauch, Gerhard Neumann
Published in Workshop on Optimization for Machine Learning @ NeurIPS, 2023
Curriculum-Based Imitation of Versatile Skills
Maximilian Xiling Li, Onur Celik, Philipp Becker, Denis Blessing, Rudolf Lioutikov, Gerhard Neumann
Published in International Conference on Robotics and Automation (ICRA), 2023
Accurate Bayesian Meta-Learning by Accurate Task Posterior Inference
Michael Volpp, Philipp Dahlinger, Philipp Becker, Christian Daniel, Gerhard Neumann
Published in International Conference on Learning Representations (ICLR), 2023
Inferring Versatile Behavior from Demonstrations by Matching Geometric Descriptors
Niklas Freymuth, Nicolas Schreiber, Philipp Becker, Aleksander Taranovic, Gerhard Neumann
Published in Conference on Robot Learning (CoRL), 2022
Hidden Parameter Recurrent State Space Models For Changing Dynamics Scenarios
Vaisakh Shaj Kumar, D Büchler, R Sonker, Philipp Becker, Gerhard Neumann
Published in International Conference on Learning Representations (ICLR), 2022
End-to-End Learning of Hybrid Inverse Dynamics Models for Precise and Compliant Impedance Control
Moritz Reuss, Niels van Duijkeren, Robert Krug, Philipp Becker, Vaisakh Shaj, Gerhard Neumann
Published in Robotics: Science and Systems (RSS), 2022
Switching Recurrent Kalman Networks
Giao Nguyen-Quynh, Philipp Becker, Chen Qiu, Maja Rudolph, Gerhard Neumann
Published in Machine Learning for Autonomous Driving Workshop @ NeurIPS, 2021
Versatile Inverse Reinforcement Learning via Cumulative Rewards
Niklas Freymuth, Philipp Becker , Gerhard Neumann
Published in Workshop on Robot Learning: Self-Supervised and Lifelong Learning @ NeurIPS, 2021
Specializing Versatile Skill Libraries using Local Mixture of Experts
Onur Celik, Dongzhuoran Zhou, Ge Li, Philipp Becker, Gerhard Neumann
Published in Conference on Robot Learning (CoRL), 2021
Action-Conditional Recurrent Kalman Networks For Forward and Inverse Dynamics Learning
Vaisakh Shaj, Philipp Becker, Dieter Büchler, Harit Pandya, Niels van Duijkeren, C James Taylor, Marc Hanheide, Gerhard Neumann
Published in Conference on Robot Learning (CoRL), 2020