Becker, Philipp

20 publications

NeurIPS 2025 AMBER: Adaptive Mesh Generation by Iterative Mesh Resolution Prediction Niklas Freymuth, Tobias Würth, Nicolas Schreiber, Balázs Gyenes, Andreas Boltres, Johannes Mitsch, Aleksandar Taranovic, Tai Hoang, Philipp Dahlinger, Philipp Becker, Luise Kärger, Gerhard Neumann

ICCV 2025 EDiT: Efficient Diffusion Transformers with Linear Compressed Attention Philipp Becker, Abhinav Mehrotra, Ruchika Chavhan, Malcolm Chadwick, Luca Morreale, Mehdi Noroozi, Alberto Gil C. P. Ramos, Sourav Bhattacharya

ICLR 2025 Efficient Off-Policy Learning for High-Dimensional Action Spaces Fabian Otto, Philipp Becker, Vien Anh Ngo, Gerhard Neumann

ICLR 2025 Geometry-Aware RL for Manipulation of Varying Shapes and Deformable Objects Tai Hoang, Huy Le, Philipp Becker, Vien Anh Ngo, Gerhard Neumann

NeurIPSW 2024 Adaptive World Models: Learning Behaviors by Latent Imagination Under Non-Stationarity Emiliyan Gospodinov, Vaisakh Shaj, Philipp Becker, Stefan Geyer, Gerhard Neumann

ICMLW 2024 Combining Reconstruction and Contrastive Methods for Multimodal Representations in RL Philipp Becker, Sebastian Mossburger, Fabian Otto, Gerhard Neumann

ICMLW 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

ICMLW 2024 KalMamba: Towards Efficient Probabilistic State Space Models for RL Under Uncertainty Philipp Becker, Niklas Freymuth, Gerhard Neumann

CoRL 2024 PointPatchRL - Masked Reconstruction Improves Reinforcement Learning on Point Clouds Balazs Gyenes, Nikolai Franke, Philipp Becker, Gerhard Neumann

ICLR 2023 Accurate Bayesian Meta-Learning by Accurate Task Posterior Inference Michael Volpp, Philipp Dahlinger, Philipp Becker, Christian Daniel, Gerhard Neumann

NeurIPS 2023 Beyond Deep Ensembles: A Large-Scale Evaluation of Bayesian Deep Learning Under Distribution Shift Florian Seligmann, Philipp Becker, Michael Volpp, Gerhard Neumann

NeurIPSW 2023 Information-Theoretic Trust Regions for Stochastic Gradient-Based Optimization Philipp Dahlinger, Philipp Becker, Maximilian Hüttenrauch, Gerhard Neumann

ICLR 2022 Hidden Parameter Recurrent State Space Models for Changing Dynamics Scenarios Vaisakh Shaj, Dieter Büchler, Rohit Sonker, Philipp Becker, Gerhard Neumann

CoRL 2022 Inferring Versatile Behavior from Demonstrations by Matching Geometric Descriptors Niklas Freymuth, Nicolas Schreiber, Aleksandar Taranovic, Philipp Becker, Gerhard Neumann

TMLR 2022 On Uncertainty in Deep State Space Models for Model-Based Reinforcement Learning Philipp Becker, Gerhard Neumann

ICLR 2021 Differentiable Trust Region Layers for Deep Reinforcement Learning Fabian Otto, Philipp Becker, Vien Anh Ngo, Hanna Carolin Maria Ziesche, Gerhard Neumann

CoRL 2021 Specializing Versatile Skill Libraries Using Local Mixture of Experts Onur Celik, Dongzhuoran Zhou, Ge Li, Philipp Becker, Gerhard Neumann

CoRL 2020 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

ICLR 2020 Expected Information Maximization: Using the I-Projection for Mixture Density Estimation Philipp Becker, Oleg Arenz, Gerhard Neumann

ICML 2019 Recurrent Kalman Networks: Factorized Inference in High-Dimensional Deep Feature Spaces Philipp Becker, Harit Pandya, Gregor Gebhardt, Cheng Zhao, C. James Taylor, Gerhard Neumann