Geometry-aware RL for Manipulation of Varying Shapes and Deformable Objects
Tai Hoang, Huy Le, Philipp Becker, Vien Anh Ngo, Gerhard Neumann
Published in International Conference on Learning Representations (ICLR), 2025
Representation and Dynamics Learning for Robotics
Adaptive World Models: Learning Behaviors by Latent Imagination Under Non-Stationarity
Emiliyan Gospodinov, Vaisakh Shaj, Philipp Becker, Stefan Geyer, Gerhard Neumann
Published in Workshop on Adaptive Foundation Models @ NeurIPS, 2024
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
Paper | Code | Project Page
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
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
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
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
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
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