Neumann, Gerhard

94 publications

TMLR 2026 Context-Aware Learned Mesh-Based Simulation via Trajectory-Level Meta-Learning Philipp Dahlinger, Niklas Freymuth, Tai Hoang, Tobias Würth, Michael Volpp, Luise Kärger, Gerhard Neumann

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

ICML 2025 DIME: Diffusion-Based Maximum Entropy Reinforcement Learning Onur Celik, Zechu Li, Denis Blessing, Ge Li, Daniel Palenicek, Jan Peters, Georgia Chalvatzaki, Gerhard Neumann

NeurIPS 2025 Diffusion-Based Hierarchical Graph Neural Networks for Simulating Nonlinear Solid Mechanics Tobias Würth, Niklas Freymuth, Gerhard Neumann, Luise Kärger

ICLRW 2025 Diffusion-Based Maximum Entropy Reinforcement Learning Onur Celik, Zechu Li, Denis Blessing, Ge Li, Daniel Palenicek, Jan Peters, Georgia Chalvatzaki, Gerhard Neumann

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

ICLR 2025 End-to-End Learning of Gaussian Mixture Priors for Diffusion Sampler Denis Blessing, Xiaogang Jia, 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

CoRL 2025 IRIS: An Immersive Robot Interaction System Xinkai Jiang, Qihao Yuan, Enes Ulas Dincer, Hongyi Zhou, Ge Li, Xueyin Li, Xiaogang Jia, Timo Schnizer, Nicolas Schreiber, Weiran Liao, Julius Haag, Kailai Li, Gerhard Neumann, Rudolf Lioutikov

NeurIPS 2025 MaNGO — Adaptable Graph Network Simulators via Meta-Learning Philipp Dahlinger, Tai Hoang, Denis Blessing, Niklas Freymuth, Gerhard Neumann

NeurIPS 2025 PointMapPolicy: Structured Point Cloud Processing for Multi-Modal Imitation Learning Xiaogang Jia, Qian Wang, Anrui Wang, Han A. Wang, Balázs Gyenes, Emiliyan Gospodinov, Xinkai Jiang, Ge Li, Hongyi Zhou, Weiran Liao, Xi Huang, Maximilian Beck, Moritz Reuss, Rudolf Lioutikov, Gerhard Neumann

NeurIPS 2025 Scaffolding Dexterous Manipulation with Vision-Language Models Vincent de Bakker, Joey Hejna, Tyler Ga Wei Lum, Onur Celik, Aleksandar Taranovic, Denis Blessing, Gerhard Neumann, Jeannette Bohg, Dorsa Sadigh

ICLR 2025 Sequential Controlled Langevin Diffusions Junhua Chen, Lorenz Richter, Julius Berner, Denis Blessing, Gerhard Neumann, Anima Anandkumar

ICLR 2025 TOP-ERL: Transformer-Based Off-Policy Episodic Reinforcement Learning Ge Li, Dong Tian, Hongyi Zhou, Xinkai Jiang, Rudolf Lioutikov, Gerhard Neumann

ICLRW 2025 TOP-ERL: Transformer-Based Off-Policy Episodic Reinforcement Learning Ge Li, Dong Tian, Hongyi Zhou, Xinkai Jiang, Rudolf Lioutikov, Gerhard Neumann

ICLRW 2025 Towards Fusing Point Cloud and Visual Representations for Imitation Learning Atalay Donat, Xiaogang Jia, Xi Huang, Aleksandar Taranovic, Denis Blessing, Ge Li, Hongyi Zhou, Hanyi Zhang, Rudolf Lioutikov, Gerhard Neumann

TMLR 2025 Towards Measuring Predictability: To Which Extent Data-Driven Approaches Can Extract Deterministic Relations from Data Exemplified with Time Series Prediction and Classification Saleh GHOLAM Zadeh, Vaisakh Shaj, Patrick Jahnke, Gerhard Neumann, Tim Breitenbach

NeurIPS 2025 Trust Region Constrained Measure Transport in Path Space for Stochastic Optimal Control and Inference Denis Blessing, Julius Berner, Lorenz Richter, Carles Domingo-Enrich, Yuanqi Du, Arash Vahdat, Gerhard Neumann

ICLR 2025 Underdamped Diffusion Bridges with Applications to Sampling Denis Blessing, Julius Berner, Lorenz Richter, Gerhard Neumann

ICLRW 2025 Underdamped Diffusion Bridges with Applications to Sampling Denis Blessing, Julius Berner, Lorenz Richter, Gerhard Neumann

ICLRW 2025 X-IL: Exploring the Design Space of Imitation Learning Policies Xiaogang Jia, Atalay Donat, Xi Huang, Xuan Zhao, Denis Blessing, Hongyi Zhou, Hanyi Zhang, Han A. Wang, Qian Wang, Rudolf Lioutikov, Gerhard Neumann

NeurIPS 2024 A Retrospective on the Robot Air Hockey Challenge: Benchmarking Robust, Reliable, and Safe Learning Techniques for Real-World Robotics Puze Liu, Jonas Günster, Niklas Funk, Simon Gröger, Dong Chen, Haitham Bou-Ammar, Julius Jankowski, Ante Marić, Sylvain Calinon, Andrej Orsula, Miguel Olivares-Mendez, Hongyi Zhou, Rudolf Lioutikov, Gerhard Neumann, Amarildo Likmeta, Amirhossein Zhalehmehrabi, Thomas Bonenfant, Marcello Restelli, Davide Tateo, Ziyuan Liu, Jan Peters

ICML 2024 Acquiring Diverse Skills Using Curriculum Reinforcement Learning with Mixture of Experts Onur Celik, Aleksandar Taranovic, Gerhard Neumann

ICMLW 2024 Acquiring Diverse Skills Using Curriculum Reinforcement Learning with Mixture of Experts Onur Celik, Aleksandar Taranovic, 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

ICML 2024 Beyond ELBOs: A Large-Scale Evaluation of Variational Methods for Sampling Denis Blessing, Xiaogang Jia, Johannes Esslinger, Francisco Vargas, 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

TMLR 2024 Learning Sub-Second Routing Optimization in Computer Networks Requires Packet-Level Dynamics Andreas Boltres, Niklas Freymuth, Patrick Jahnke, Holger Karl, Gerhard Neumann

CoRL 2024 MaIL: Improving Imitation Learning with Selective State Space Models Xiaogang Jia, Qian Wang, Atalay Donat, Bowen Xing, Ge Li, Hongyi Zhou, Onur Celik, Denis Blessing, Rudolf Lioutikov, Gerhard Neumann

ICLR 2024 Neural Contractive Dynamical Systems Hadi Beik Mohammadi, Søren Hauberg, Georgios Arvanitidis, Nadia Figueroa, Gerhard Neumann, Leonel Rozo

ICLR 2024 Open the Black Box: Step-Based Policy Updates for Temporally-Correlated Episodic Reinforcement Learning Ge Li, Hongyi Zhou, Dominik Roth, Serge Thilges, Fabian Otto, Rudolf Lioutikov, Gerhard Neumann

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

WACV 2024 Registered and Segmented Deformable Object Reconstruction from a Single View Point Cloud Pit Henrich, Balázs Gyenes, Paul Maria Scheikl, Gerhard Neumann, Franziska Mathis-Ullrich

JMLR 2024 Robust Black-Box Optimization for Stochastic Search and Episodic Reinforcement Learning Maximilian Hüttenrauch, Gerhard Neumann

ICLR 2024 Towards Diverse Behaviors: A Benchmark for Imitation Learning with Human Demonstrations Xiaogang Jia, Denis Blessing, Xinkai Jiang, Moritz Reuss, Atalay Donat, Rudolf Lioutikov, Gerhard Neumann

NeurIPS 2024 Variational Distillation of Diffusion Policies into Mixture of Experts Hongyi Zhou, Denis Blessing, Ge Li, Onur Celik, Xiaogang Jia, Gerhard Neumann, Rudolf Lioutikov

TMLR 2023 A Unified Perspective on Natural Gradient Variational Inference with Gaussian Mixture Models Oleg Arenz, Philipp Dahlinger, Zihan Ye, Michael Volpp, Gerhard Neumann

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

ICLR 2023 Adversarial Imitation Learning with Preferences Aleksandar Taranovic, Andras Gabor Kupcsik, Niklas Freymuth, 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

ICLR 2023 Grounding Graph Network Simulators Using Physical Sensor Observations Jonas Linkerhägner, Niklas Freymuth, Paul Maria Scheikl, Franziska Mathis-Ullrich, Gerhard Neumann

ICLRW 2023 Grounding Graph Network Simulators Using Physical Sensor Observations Jonas Linkerhägner, Niklas Freymuth, Paul Maria Scheikl, Franziska Mathis-Ullrich, Gerhard Neumann

NeurIPS 2023 Information Maximizing Curriculum: A Curriculum-Based Approach for Learning Versatile Skills Denis Blessing, Onur Celik, Xiaogang Jia, Moritz Reuss, Maximilian Li, Rudolf Lioutikov, Gerhard Neumann

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

JMLR 2023 LapGym - An Open Source Framework for Reinforcement Learning in Robot-Assisted Laparoscopic Surgery Paul Maria Scheikl, Balázs Gyenes, Rayan Younis, Christoph Haas, Gerhard Neumann, Martin Wagner, Franziska Mathis-Ullrich

NeurIPSW 2023 Latent Task-Specific Graph Network Simulators Philipp Dahlinger, Niklas Freymuth, Tai Hoang, Michael Volpp, Gerhard Neumann

NeurIPS 2023 Multi Time Scale World Models Vaisakh Shaj Kumar, Saleh Gholam Zadeh, Ozan Demir, Luiz Douat, Gerhard Neumann

NeurIPSW 2023 Reinforcement Learning of Diverse Skills Using Mixture of Deep Experts Onur Celik, Aleksandar Taranovic, Gerhard Neumann

CoRL 2023 SA6D: Self-Adaptive Few-Shot 6d Pose Estimator for Novel and Occluded Objects Ning Gao, Vien Anh Ngo, Hanna Ziesche, Gerhard Neumann

NeurIPS 2023 Swarm Reinforcement Learning for Adaptive Mesh Refinement Niklas Freymuth, Philipp Dahlinger, Tobias Würth, Simon Reisch, Luise Kärger, Gerhard Neumann

ICLRW 2023 Swarm Reinforcement Learning for Adaptive Mesh Refinement Niklas Freymuth, Philipp Dahlinger, Tobias Würth, Luise Kärger, Gerhard Neumann

CoRL 2022 Deep Black-Box Reinforcement Learning with Movement Primitives Fabian Otto, Onur Celik, Hongyi Zhou, Hanna Ziesche, Vien Anh Ngo, Gerhard Neumann

ECCV 2022 FusionVAE: A Deep Hierarchical Variational Autoencoder for RGB Image Fusion Fabian Duffhauss, Ngo Anh Vien, Hanna Ziesche, 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

CVPR 2022 What Matters for Meta-Learning Vision Regression Tasks? Ning Gao, Hanna Ziesche, Ngo Anh Vien, Michael Volpp, Gerhard Neumann

ICLR 2021 Bayesian Context Aggregation for Neural Processes Michael Volpp, Fabian Flürenbrock, Lukas Grossberger, Christian Daniel, 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

JMLR 2020 Trust-Region Variational Inference with Gaussian Mixture Models Oleg Arenz, Mingjun Zhong, Gerhard Neumann

MLJ 2019 Compatible Natural Gradient Policy Search Joni Pajarinen, Hong Linh Thai, Riad Akrour, Jan Peters, Gerhard Neumann

JMLR 2019 Deep Reinforcement Learning for Swarm Systems Maximilian Hüttenrauch, Adrian Šošić, Gerhard Neumann

ICML 2019 Projections for Approximate Policy Iteration Algorithms Riad Akrour, Joni Pajarinen, Jan Peters, 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

MLJ 2019 The Kernel Kalman Rule - Efficient Nonparametric Inference by Recursive Least-Squares and Subspace Projections Gregor H. W. Gebhardt, Andras Gabor Kupcsik, Gerhard Neumann

ICML 2018 Efficient Gradient-Free Variational Inference Using Policy Search Oleg Arenz, Gerhard Neumann, Mingjun Zhong

JMLR 2018 Model-Free Trajectory-Based Policy Optimization with Monotonic Improvement Riad Akrour, Abbas Abdolmaleki, Hany Abdulsamad, Jan Peters, Gerhard Neumann

JMLR 2017 A Survey of Preference-Based Reinforcement Learning Methods Christian Wirth, Riad Akrour, Gerhard Neumann, Johannes Fürnkranz

IJCAI 2017 Contextual Covariance Matrix Adaptation Evolutionary Strategies Abbas Abdolmaleki, Bob Price, Nuno Lau, Luís Paulo Reis, Gerhard Neumann

ICML 2017 Local Bayesian Optimization of Motor Skills Riad Akrour, Dmitry Sorokin, Jan Peters, Gerhard Neumann

JMLR 2017 Non-Parametric Policy Search with Limited Information Loss Herke van Hoof, Gerhard Neumann, Jan Peters

AAAI 2017 Policy Search with High-Dimensional Context Variables Voot Tangkaratt, Herke van Hoof, Simone Parisi, Gerhard Neumann, Jan Peters, Masashi Sugiyama

AAAI 2017 The Kernel Kalman Rule - Efficient Nonparametric Inference with Recursive Least Squares Gregor H. W. Gebhardt, Andras Gabor Kupcsik, Gerhard Neumann

NeurIPS 2016 Catching Heuristics Are Optimal Control Policies Boris Belousov, Gerhard Neumann, Constantin A Rothkopf, Jan R Peters

JMLR 2016 Hierarchical Relative Entropy Policy Search Christian Daniel, Gerhard Neumann, Oliver Kroemer, Jan Peters

AAAI 2016 Model-Free Preference-Based Reinforcement Learning Christian Wirth, Johannes Fürnkranz, Gerhard Neumann

ICML 2016 Model-Free Trajectory Optimization for Reinforcement Learning Riad Akrour, Gerhard Neumann, Hany Abdulsamad, Abbas Abdolmaleki

MLJ 2016 Probabilistic Inference for Determining Options in Reinforcement Learning Christian Daniel, Herke van Hoof, Jan Peters, Gerhard Neumann

AISTATS 2015 Learning of Non-Parametric Control Policies with High-Dimensional State Features Herke van Hoof, Jan Peters, Gerhard Neumann

NeurIPS 2015 Model-Based Relative Entropy Stochastic Search Abbas Abdolmaleki, Rudolf Lioutikov, Jan R Peters, Nuno Lau, Luis Pualo Reis, Gerhard Neumann

JMLR 2014 Policy Evaluation with Temporal Differences: A Survey and Comparison Christoph Dann, Gerhard Neumann, Jan Peters

ECML-PKDD 2014 Policy Search for Path Integral Control Vicenç Gómez, Hilbert J. Kappen, Jan Peters, Gerhard Neumann

AAAI 2013 Data-Efficient Generalization of Robot Skills with Contextual Policy Search Andras Gabor Kupcsik, Marc Peter Deisenroth, Jan Peters, Gerhard Neumann

NeurIPS 2013 Probabilistic Movement Primitives Alexandros Paraschos, Christian Daniel, Jan R Peters, Gerhard Neumann

ECML-PKDD 2013 Towards Robot Skill Learning: From Simple Skills to Table Tennis Jan Peters, Jens Kober, Katharina Mülling, Oliver Krömer, Gerhard Neumann

AISTATS 2012 Hierarchical Relative Entropy Policy Search Christian Daniel, Gerhard Neumann, Jan Peters

ICML 2011 Variational Inference for Policy Search in Changing Situations Gerhard Neumann

ICML 2009 Learning Complex Motions by Sequencing Simpler Motion Templates Gerhard Neumann, Wolfgang Maass, Jan Peters

NeurIPS 2008 Fitted Q-Iteration by Advantage Weighted Regression Gerhard Neumann, Jan R. Peters