ML Anthology

Peters, Jan

113 publications

ICLR 2025 Adaptive $q$-Network: On-the-Fly Target Selection for Deep Reinforcement Learning Théo Vincent, Fabian Wahren, Jan Peters, Boris Belousov, Carlo D'Eramo
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
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 Inverse Decision-Making Using Neural Amortized Bayesian Actors Dominik Straub, Tobias F. Niehues, Jan Peters, Constantin A. Rothkopf
TMLR 2025 Iterated $q$-Network: Beyond One-Step Bellman Updates in Deep Reinforcement Learning Théo Vincent, Daniel Palenicek, Boris Belousov, Jan Peters, Carlo D'Eramo
TMLR 2025 Machine Learning with Physics Knowledge for Prediction: A Survey Joe Watson, Chen Song, Oliver Weeger, Theo Gruner, An Thai Le, Kay Hansel, Ahmed Hendawy, Oleg Arenz, Will Trojak, Miles Cranmer, Carlo D'Eramo, Fabian Buelow, Tanmay Goyal, Jan Peters, Martin W Hoffmann
ICML 2025 Maximum Total Correlation Reinforcement Learning Bang You, Puze Liu, Huaping Liu, Jan Peters, Oleg Arenz
TMLR 2025 Model Tensor Planning An Thai Le, Khai Nguyen, Minh Nhat Vu, Joao Carvalho, Jan Peters
ICLR 2025 Noise-Conditioned Energy-Based Annealed Rewards (NEAR): A Generative Framework for Imitation Learning from Observation Anish Abhijit Diwan, Julen Urain, Jens Kober, Jan Peters
TMLR 2025 Rollout Total Correlation for Deep Reinforcement Learning Bang You, Huaping Liu, Jan Peters, Oleg Arenz
NeurIPS 2025 Scaling Off-Policy Reinforcement Learning with Batch and Weight Normalization Daniel Palenicek, Florian Vogt, Joe Watson, Jan Peters
NeurIPS 2025 Stable Port-Hamiltonian Neural Networks Fabian J. Roth, Dominik K. Klein, Maximilian Kannapinn, Jan Peters, Oliver Weeger
CoRL 2025 Towards Embodiment Scaling Laws in Robot Locomotion Bo Ai, Liu Dai, Nico Bohlinger, Dichen Li, Tongzhou Mu, Zhanxin Wu, K. Fay, Henrik I Christensen, Jan Peters, Hao Su
TMLR 2025 Uncertainty Representations in State-Space Layers for Deep Reinforcement Learning Under Partial Observability Carlos E. Luis, Alessandro Giacomo Bottero, Julia Vinogradska, Felix Berkenkamp, Jan Peters
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
JAIR 2024 A Unified Perspective on Value Backup and Exploration in Monte-Carlo Tree Search Tuan Dam, Carlo D'Eramo, Jan Peters, Joni Pajarinen
ICMLW 2024 Adaptive $q$-Network: On-the-Fly Target Selection for Deep Reinforcement Learning Théo Vincent, Fabian Wahren, Jan Peters, Boris Belousov, Carlo D'Eramo
CoRL 2024 Bridging the Gap Between Learning-to-Plan, Motion Primitives and Safe Reinforcement Learning Piotr Kicki, Davide Tateo, Puze Liu, Jonas Günster, Jan Peters, Krzysztof Walas
ICLR 2024 CrossQ: Batch Normalization in Deep Reinforcement Learning for Greater Sample Efficiency and Simplicity Aditya Bhatt, Daniel Palenicek, Boris Belousov, Max Argus, Artemij Amiranashvili, Thomas Brox, Jan Peters
ICLR 2024 Domain Randomization via Entropy Maximization Gabriele Tiboni, Pascal Klink, Jan Peters, Tatiana Tommasi, Carlo D'Eramo, Georgia Chalvatzaki
ACML 2024 Dude: Dual Distribution-Aware Context Prompt Learning for Large Vision-Language Model Duy Minh Ho Nguyen, An Thai Le, Trung Quoc Nguyen, Nghiem Tuong Diep, Tai Nguyen, Duy Duong-Tran, Jan Peters, Li Shen, Mathias Niepert, Daniel Sonntag
ECCVW 2024 FruitBin: A Tunable Large-Scale Dataset for Advancing 6d Pose Estimation in Fruit Bin-Picking Automation Guillaume Duret, Mahmoud Ali, Nicolas Cazin, Danylo Mazurak, Anna Samsonenko, Alexandre Chapin, Florence Zara, Emmanuel Dellandréa, Liming Chen, Jan Peters
CoRL 2024 Handling Long-Term Safety and Uncertainty in Safe Reinforcement Learning Jonas Günster, Puze Liu, Jan Peters, Davide Tateo
NeurIPSW 2024 Learning Force Distribution Estimation for the GelSight Mini Optical Tactile Sensor Based on Finite Element Analysis Erik Helmut, Luca Dziarski, Niklas Funk, Boris Belousov, Jan Peters
ICLR 2024 Multi-Task Reinforcement Learning with Mixture of Orthogonal Experts Ahmed Hendawy, Jan Peters, Carlo D'Eramo
CoRL 2024 One Policy to Run Them All: An End-to-End Learning Approach to Multi-Embodiment Locomotion Nico Bohlinger, Grzegorz Czechmanowski, Maciej Piotr Krupka, Piotr Kicki, Krzysztof Walas, Jan Peters, Davide Tateo
AAAI 2024 Parameterized Projected Bellman Operator Théo Vincent, Alberto Maria Metelli, Boris Belousov, Jan Peters, Marcello Restelli, Carlo D'Eramo
AAAI 2024 Peer Learning: Learning Complex Policies in Groups from Scratch via Action Recommendations Cedric Derstroff, Mattia Cerrato, Jannis Brugger, Jan Peters, Stefan Kramer
CoRL 2024 PianoMime: Learning a Generalist, Dexterous Piano Player from Internet Demonstrations Cheng Qian, Julen Urain, Kevin Zakka, Jan Peters
IJCAI 2024 Reinforcement Learning for Athletic Intelligence: Lessons from the 1st "AI Olympics with RealAIGym" Competition Felix Wiebe, Niccolò Turcato, Alberto Dalla Libera, Chi Zhang, Théo Vincent, Shubham Vyas, Giulio Giacomuzzo, Ruggero Carli, Diego Romeres, Akhil Sathuluri, Markus Zimmermann, Boris Belousov, Jan Peters, Frank Kirchner, Shivesh Kumar
ICLR 2024 Robust Adversarial Reinforcement Learning via Bounded Rationality Curricula Aryaman Reddi, Maximilian Tölle, Jan Peters, Georgia Chalvatzaki, Carlo D'Eramo
ICML 2024 Structure-Aware E(3)-Invariant Molecular Conformer Aggregation Networks Duy Minh Ho Nguyen, Nina Lukashina, Tai Nguyen, An Thai Le, Trungtin Nguyen, Nhat Ho, Jan Peters, Daniel Sonntag, Viktor Zaverkin, Mathias Niepert
ICLR 2024 Time-Efficient Reinforcement Learning with Stochastic Stateful Policies Firas Al-Hafez, Guoping Zhao, Jan Peters, Davide Tateo
JMLR 2024 Value-Distributional Model-Based Reinforcement Learning Carlos E. Luis, Alessandro G. Bottero, Julia Vinogradska, Felix Berkenkamp, Jan Peters
NeurIPSW 2023 Accelerating Motion Planning via Optimal Transport An Le, Georgia Chalvatzaki, Armin Biess, Jan Peters
TMLR 2023 Cheap and Deterministic Inference for Deep State-Space Models of Interacting Dynamical Systems Andreas Look, Barbara Rakitsch, Melih Kandemir, Jan Peters
ICLR 2023 Diminishing Return of Value Expansion Methods in Model-Based Reinforcement Learning Daniel Palenicek, Michael Lutter, Joao Carvalho, Jan Peters
L4DC 2023 Hierarchical Policy Blending as Optimal Transport An Thai Le, Kay Hansel, Jan Peters, Georgia Chalvatzaki
ICLR 2023 LS-IQ: Implicit Reward Regularization for Inverse Reinforcement Learning Firas Al-Hafez, Davide Tateo, Oleg Arenz, Guoping Zhao, Jan Peters
AISTATS 2023 Model-Based Uncertainty in Value Functions Carlos E. Luis, Alessandro G. Bottero, Julia Vinogradska, Felix Berkenkamp, Jan Peters
ICMLW 2023 Parameterized Projected Bellman Operator Théo Vincent, Alberto Maria Metelli, Jan Peters, Marcello Restelli, Carlo D'Eramo
NeurIPSW 2023 Using Proto-Value Functions for Curriculum Generation in Goal-Conditioned RL Henrik Metternich, Ahmed Hendawy, Pascal Klink, Jan Peters, Carlo D'Eramo
AISTATS 2022 Dimensionality Reduction and Prioritized Exploration for Policy Search Marius Memmel, Puze Liu, Davide Tateo, Jan Peters
ICLR 2022 Boosted Curriculum Reinforcement Learning Pascal Klink, Carlo D'Eramo, Jan Peters, Joni Pajarinen
NeurIPSW 2022 Conditioned Score-Based Models for Learning Collision-Free Trajectory Generation Joao Carvalho, Mark Baierl, Julen Urain, Jan Peters
ICML 2022 Curriculum Reinforcement Learning via Constrained Optimal Transport Pascal Klink, Haoyi Yang, Carlo D’Eramo, Jan Peters, Joni Pajarinen
JAIR 2022 HEBO: An Empirical Study of Assumptions in Bayesian Optimisation Alexander I. Cowen-Rivers, Wenlong Lyu, Rasul Tutunov, Zhi Wang, Antoine Grosnit, Ryan-Rhys Griffiths, Alexandre Max Maraval, Jianye Hao, Jun Wang, Jan Peters, Haitham Bou-Ammar
NeurIPSW 2022 How Crucial Is Transformer in Decision Transformer? Max Siebenborn, Boris Belousov, Junning Huang, Jan Peters
CoRL 2022 Inferring Smooth Control: Monte Carlo Posterior Policy Iteration with Gaussian Processes Joe Watson, Jan Peters
ICLRW 2022 Revisiting Model-Based Value Expansion Daniel Palenicek, Michael Lutter, Jan Peters
AISTATS 2021 Latent Derivative Bayesian Last Layer Networks Joe Watson, Jihao Andreas Lin, Pascal Klink, Joni Pajarinen, Jan Peters
JMLR 2021 A Probabilistic Interpretation of Self-Paced Learning with Applications to Reinforcement Learning Pascal Klink, Hany Abdulsamad, Boris Belousov, Carlo D'Eramo, Jan Peters, Joni Pajarinen
MLJ 2021 Convex Optimization with an Interpolation-Based Projection and Its Application to Deep Learning Riad Akrour, Asma Atamna, Jan Peters
ICML 2021 Convex Regularization in Monte-Carlo Tree Search Tuan Q Dam, Carlo D’Eramo, Jan Peters, Joni Pajarinen
ICMLW 2021 Exploration via Empowerment Gain: Combining Novelty, Surprise and Learning Progress Philip Becker-Ehmck, Maximilian Karl, Jan Peters, Patrick van der Smagt
JMLR 2021 Gaussian Approximation for Bias Reduction in Q-Learning Carlo D'Eramo, Andrea Cini, Alessandro Nuara, Matteo Pirotta, Cesare Alippi, Jan Peters, Marcello Restelli
CoRL 2021 Learn2Assemble with Structured Representations and Search for Robotic Architectural Construction Niklas Funk, Georgia Chalvatzaki, Boris Belousov, Jan Peters
MLOSS 2021 MushroomRL: Simplifying Reinforcement Learning Research Carlo D'Eramo, Davide Tateo, Andrea Bonarini, Marcello Restelli, Jan Peters
CoRL 2021 Neural Posterior Domain Randomization Fabio Muratore, Theo Gruner, Florian Wiese, Boris Belousov, Michael Gienger, Jan Peters
CoRL 2021 Robot Reinforcement Learning on the Constraint Manifold Puze Liu, Davide Tateo, Haitham Bou Ammar, Jan Peters
ICML 2021 Value Iteration in Continuous Actions, States and Time Michael Lutter, Shie Mannor, Jan Peters, Dieter Fox, Animesh Garg
AISTATS 2020 A Nonparametric Off-Policy Policy Gradient Samuele Tosatto, Joao Carvalho, Hany Abdulsamad, Jan Peters
UAI 2020 Bayesian Online Prediction of Change Points Diego Agudelo-España, Sebastian Gomez-Gonzalez, Stefan Bauer, Bernhard Schölkopf, Jan Peters
ICLRW 2020 Differential Equations as a Model Prior for Deep Learning and Its Applications in Robotics Michael Lutter, Jan Peters
IJCAI 2020 Generalized Mean Estimation in Monte-Carlo Tree Search Tuan Dam, Pascal Klink, Carlo D'Eramo, Jan Peters, Joni Pajarinen
L4DC 2020 Hierarchical Decomposition of Nonlinear Dynamics and Control for System Identification and Policy Distillation Hany Abdulsamad, Jan Peters
CoRL 2020 High Acceleration Reinforcement Learning for Real-World Juggling with Binary Rewards Kai Ploeger, Michael Lutter, Jan Peters
ICLR 2020 Learning Human Postural Control with Hierarchical Acquisition Functions Nils Rottmann, Tjasa Kunavar, Jan Babic, Jan Peters, Elmar Rueckert
ICLR 2020 Sharing Knowledge in Multi-Task Deep Reinforcement Learning Carlo D'Eramo, Davide Tateo, Andrea Bonarini, Marcello Restelli, Jan Peters
MLJ 2019 Compatible Natural Gradient Policy Search Joni Pajarinen, Hong Linh Thai, Riad Akrour, Jan Peters, Gerhard Neumann
ICLR 2019 Deep Lagrangian Networks: Using Physics as Model Prior for Deep Learning Michael Lutter, Christian Ritter, Jan Peters
CoRL 2019 HJB Optimal Feedback Control with Deep Differential Value Functions and Action Constraints Michael Lutter, Boris Belousov, Kim Listmann, Debora Clever, Jan Peters
ICML 2019 Projections for Approximate Policy Iteration Algorithms Riad Akrour, Joni Pajarinen, Jan Peters, Gerhard Neumann
CoRL 2019 Receding Horizon Curiosity Matthias Schultheis, Boris Belousov, Hany Abdulsamad, Jan Peters
CoRL 2019 Self-Paced Contextual Reinforcement Learning Pascal Klink, Hany Abdulsamad, Boris Belousov, Jan Peters
CoRL 2019 Stochastic Optimal Control as Approximate Input Inference Joe Watson, Hany Abdulsamad, Jan Peters
ICML 2019 Switching Linear Dynamics for Variational Bayes Filtering Philip Becker-Ehmck, Jan Peters, Patrick Van Der Smagt
MLJ 2019 TD-Regularized Actor-Critic Methods Simone Parisi, Voot Tangkaratt, Jan Peters, Mohammad Emtiyaz Khan
CoRL 2018 Domain Randomization for Simulation-Based Policy Optimization with Transferability Assessment Fabio Muratore, Felix Treede, Michael Gienger, Jan Peters
JMLR 2018 Inverse Reinforcement Learning via Nonparametric Spatio-Temporal Subgoal Modeling Adrian Šošić, Elmar Rueckert, Jan Peters, Abdelhak M. Zoubir, Heinz Koeppl
JMLR 2018 Model-Free Trajectory-Based Policy Optimization with Monotonic Improvement Riad Akrour, Abbas Abdolmaleki, Hany Abdulsamad, Jan Peters, Gerhard Neumann
ICML 2018 PIPPS: Flexible Model-Based Policy Search Robust to the Curse of Chaos Paavo Parmas, Carl Edward Rasmussen, Jan Peters, Kenji Doya
CoRL 2017 Active Incremental Learning of Robot Movement Primitives Guilherme Maeda, Marco Ewerton, Takayuki Osa, Baptiste Busch, Jan Peters
MLJ 2017 Generalized Exploration in Policy Search Herke van Hoof, Daniel Tanneberg, Jan Peters
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
CoRL 2017 Online Learning with Stochastic Recurrent Neural Networks Using Intrinsic Motivation Signals Daniel Tanneberg, Jan Peters, Elmar Rueckert
AAAI 2017 Policy Search with High-Dimensional Context Variables Voot Tangkaratt, Herke van Hoof, Simone Parisi, Gerhard Neumann, Jan Peters, Masashi Sugiyama
JMLR 2017 Stability of Controllers for Gaussian Process Dynamics Julia Vinogradska, Bastian Bischoff, Duy Nguyen-Tuong, Jan Peters
JMLR 2016 Hierarchical Relative Entropy Policy Search Christian Daniel, Gerhard Neumann, Oliver Kroemer, Jan Peters
MLJ 2016 Probabilistic Inference for Determining Options in Reinforcement Learning Christian Daniel, Herke van Hoof, Jan Peters, Gerhard Neumann
ICML 2016 Stability of Controllers for Gaussian Process Forward Models Julia Vinogradska, Bastian Bischoff, Duy Nguyen-Tuong, Anne Romer, Henner Schmidt, Jan Peters
AISTATS 2015 Learning of Non-Parametric Control Policies with High-Dimensional State Features Herke van Hoof, Jan Peters, Gerhard Neumann
JMLR 2014 Natural Evolution Strategies Daan Wierstra, Tom Schaul, Tobias Glasmachers, Yi Sun, Jan Peters, Jürgen Schmidhuber
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
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
ECML-PKDD 2012 Structured Apprenticeship Learning Abdeslam Boularias, Oliver Krömer, Jan Peters
AAAI 2011 Balancing Safety and Exploitability in Opponent Modeling Zhikun Wang, Abdeslam Boularias, Katharina Mülling, Jan Peters
AAAI 2011 Modeling Opponent Actions for Table-Tennis Playing Robot Zhikun Wang, Abdeslam Boularias, Katharina Mülling, Jan Peters
MLJ 2011 Policy Search for Motor Primitives in Robotics Jens Kober, Jan Peters
IJCAI 2011 Reinforcement Learning to Adjust Robot Movements to New Situations Jens Kober, Erhan Öztop, Jan Peters
AISTATS 2011 Relative Entropy Inverse Reinforcement Learning Abdeslam Boularias, Jens Kober, Jan Peters
AISTATS 2010 Incremental Sparsification for Real-Time Online Model Learning Duy Nguyen–Tuong, Jan Peters
AAAI 2010 Relative Entropy Policy Search Jan Peters, Katharina Mülling, Yasemin Altun
AISTATS 2009 An Expectation Maximization Algorithm for Continuous Markov Decision Processes with Arbitrary Reward Matthew Hoffman, Nando Freitas, Arnaud Doucet, Jan Peters
ECML-PKDD 2009 Efficient Sample Reuse in EM-Based Policy Search Hirotaka Hachiya, Jan Peters, Masashi Sugiyama
ICML 2009 Learning Complex Motions by Sequencing Simpler Motion Templates Gerhard Neumann, Wolfgang Maass, Jan Peters
AAAI 2008 Adaptive Importance Sampling with Automatic Model Selection in Value Function Approximation Hirotaka Hachiya, Takayuki Akiyama, Masashi Sugiyama, Jan Peters
ICML 2007 Reinforcement Learning by Reward-Weighted Regression for Operational Space Control Jan Peters, Stefan Schaal
ECML-PKDD 2005 Natural Actor-Critic Jan Peters, Sethu Vijayakumar, Stefan Schaal