Jan Peters

Motion Planning Diffusion: Learning and Adapting Robot Motion Planning with Diffusion Models (Abstract Reprint) AAAI 2026 Distilling Contact Planning for Fast Trajectory Optimization in Robot Air Hockey RSS 2025 Maximum Total Correlation Reinforcement Learning ICML 2025 DIME: Diffusion-Based Maximum Entropy Reinforcement Learning ICML 2025 Adaptive $Q$-Network: On-the-fly Target Selection for Deep Reinforcement Learning ICLR 2025 Noise-conditioned Energy-based Annealed Rewards (NEAR): A Generative Framework for Imitation Learning from Observation ICLR 2025 Towards Embodiment Scaling Laws in Robot Locomotion CORL 2025 Inverse decision-making using neural amortized Bayesian actors ICLR 2025 A Retrospective on the Robot Air Hockey Challenge: Benchmarking Robust, Reliable, and Safe Learning Techniques for Real-world Robotics NIPS 2024 PianoMime: Learning a Generalist, Dexterous Piano Player from Internet Demonstrations CORL 2024 Bridging the gap between Learning-to-plan, Motion Primitives and Safe Reinforcement Learning CORL 2024 One Policy to Run Them All: an End-to-end Learning Approach to Multi-Embodiment Locomotion CORL 2024 Handling Long-Term Safety and Uncertainty in Safe Reinforcement Learning CORL 2024 Peer Learning: Learning Complex Policies in Groups from Scratch via Action Recommendations AAAI 2024 Parameterized Projected Bellman Operator AAAI 2024 Dude: Dual Distribution-Aware Context Prompt Learning For Large Vision-Language Model ACML 2024 CrossQ: Batch Normalization in Deep Reinforcement Learning for Greater Sample Efficiency and Simplicity ICLR 2024 Time-Efficient Reinforcement Learning with Stochastic Stateful Policies ICLR 2024 Domain Randomization via Entropy Maximization ICLR 2024 Multi-Task Reinforcement Learning with Mixture of Orthogonal Experts ICLR 2024 Robust Adversarial Reinforcement Learning via Bounded Rationality Curricula ICLR 2024 Structure-Aware E(3)-Invariant Molecular Conformer Aggregation Networks ICML 2024 Reinforcement Learning for Athletic Intelligence: Lessons from the 1st “AI Olympics with RealAIGym” Competition IJCAI 2024 Value-Distributional Model-Based Reinforcement Learning JMLR 2024 LS-IQ: Implicit Reward Regularization for Inverse Reinforcement Learning ICLR 2023 Diminishing Return of Value Expansion Methods in Model-Based Reinforcement Learning ICLR 2023 Hierarchical Policy Blending As Optimal Transport L4DC 2023 Model-Based Uncertainty in Value Functions AISTATS 2023 Boosted Curriculum Reinforcement Learning ICLR 2022 Dimensionality Reduction and Prioritized Exploration for Policy Search AISTATS 2022 Curriculum Reinforcement Learning via Constrained Optimal Transport ICML 2022 Inferring Smooth Control: Monte Carlo Posterior Policy Iteration with Gaussian Processes CORL 2022 Robot Reinforcement Learning on the Constraint Manifold CORL 2021 Learn2Assemble with Structured Representations and Search for Robotic Architectural Construction CORL 2021 Neural Posterior Domain Randomization CORL 2021 Gaussian Approximation for Bias Reduction in Q-Learning JMLR 2021 Robust Value Iteration for Continuous Control Tasks RSS 2021 Composable Energy Policies for Reactive Motion Generation and Reinforcement Learning RSS 2021 A Probabilistic Interpretation of Self-Paced Learning with Applications to Reinforcement Learning JMLR 2021 Convex Regularization in Monte-Carlo Tree Search ICML 2021 Value Iteration in Continuous Actions, States and Time ICML 2021 MushroomRL: Simplifying Reinforcement Learning Research JMLR 2021 Latent Derivative Bayesian Last Layer Networks AISTATS 2021 Sharing Knowledge in Multi-Task Deep Reinforcement Learning ICLR 2020 A Nonparametric Off-Policy Policy Gradient AISTATS 2020 High Acceleration Reinforcement Learning for Real-World Juggling with Binary Rewards CORL 2020 Hierarchical Decomposition of Nonlinear Dynamics and Control for System Identification and Policy Distillation L4DC 2020 Bayesian Online Prediction of Change Points UAI 2020 Generalized Mean Estimation in Monte-Carlo Tree Search IJCAI 2020 Self-Paced Contextual Reinforcement Learning CORL 2019 Projections for Approximate Policy Iteration Algorithms ICML 2019 Switching Linear Dynamics for Variational Bayes Filtering ICML 2019 Deep Lagrangian Networks: Using Physics as Model Prior for Deep Learning ICLR 2019 Receding Horizon Curiosity CORL 2019 Stochastic Optimal Control as Approximate Input Inference CORL 2019 HJB Optimal Feedback Control with Deep Differential Value Functions and Action Constraints CORL 2019 PIPPS: Flexible Model-Based Policy Search Robust to the Curse of Chaos ICML 2018 Domain Randomization for Simulation-Based Policy Optimization with Transferability Assessment CORL 2018 Model-Free Trajectory-based Policy Optimization with Monotonic Improvement JMLR 2018 Inverse Reinforcement Learning via Nonparametric Spatio-Temporal Subgoal Modeling JMLR 2018 Local Bayesian Optimization of Motor Skills ICML 2017 Online Learning with Stochastic Recurrent Neural Networks using Intrinsic Motivation Signals CORL 2017 Non-parametric Policy Search with Limited Information Loss JMLR 2017 Stability of Controllers for Gaussian Process Dynamics JMLR 2017 Active Incremental Learning of Robot Movement Primitives CORL 2017 Stability of Controllers for Gaussian Process Forward Models ICML 2016 Hierarchical Relative Entropy Policy Search JMLR 2016 Learning of Non-Parametric Control Policies with High-Dimensional State Features AISTATS 2015 Natural Evolution Strategies JMLR 2014 Policy Evaluation with Temporal Differences: A Survey and Comparison JMLR 2014 Active Reward Learning RSS 2014 Probabilistic Modeling of Human Movements for Intention Inference RSS 2012 Hierarchical Relative Entropy Policy Search AISTATS 2012 Relative Entropy Inverse Reinforcement Learning AISTATS 2011 Incremental Sparsification for Real-time Online Model Learning AISTATS 2010