Publications

You can also find my articles on my Google Scholar profile.

Key Publications

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

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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

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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

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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

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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

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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

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All Publications

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

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Efficient Off-Policy Learning for High-Dimensional Action Spaces

Fabian Otto, Philipp Becker, Vien Anh Ngo, Gerhard Neumann
Published in International Conference on Learning Representations (ICLR), 2025

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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