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ORCIDJan Peters 0001
Person information
- affiliation: TU Darmstadt, Department of Computer Science, Germany
- affiliation: Max Planck Institute for Intelligent Systems, Tübingen, Germany
- affiliation: Max Planck Institute for Biological Cybernetics, Tübingen, Germany
- affiliation: University of Southern California Los Angeles, Computational Learning and Motion Control Lab, CA, USA
Other persons with the same name
- Jan Peters 0002 — Flemish Institute for Technological Research, Department of Environmental Quality (and 1 more)
- Jan Peters 0003 — Fraunhofer Institute for Computer Graphics Research (IGD)
- Jan Peters 0004
![[0000-0003-4895-9256]](https://dblp.dagstuhl.de/img/orcid-mark.12x12.png "0000-0003-4895-9256")
— University of Hannover, Institute of Assembly Technology, Garbsen, Germany - Jan Peters 0005 — University of Cologne, Department of Psychology, Germany
- Jan Peters 0006 — Powerledger, Perth, WA, Australia (and 1 more)
- Jan Peters 0007 — University Medical-Center Hamburg-Eppendorf, Germany
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2020 – today
- 2023
[j146]Michael Lutter, Jan Peters:
Combining physics and deep learning to learn continuous-time dynamics models. Int. J. Robotics Res. 42(3): 83-107 (2023)- [j145]Julen Urain, Anqi Li, Puze Liu, Carlo D'Eramo, Jan Peters:
Composable energy policies for reactive motion generation and reinforcement learning. Int. J. Robotics Res. 42(10): 827-858 (2023) - [j144]Andreas Look, Melih Kandemir, Barbara Rakitsch, Jan Peters:
A Deterministic Approximation to Neural SDEs. IEEE Trans. Pattern Anal. Mach. Intell. 45(4): 4023-4037 (2023) - [j143]Michael Lutter, Boris Belousov, Shie Mannor, Dieter Fox, Animesh Garg, Jan Peters:
Continuous-Time Fitted Value Iteration for Robust Policies. IEEE Trans. Pattern Anal. Mach. Intell. 45(5): 5534-5548 (2023) - [j142]Hamish Flynn, David Reeb, Melih Kandemir, Jan Peters:
PAC-Bayes Bounds for Bandit Problems: A Survey and Experimental Comparison. IEEE Trans. Pattern Anal. Mach. Intell. 45(12): 15308-15327 (2023) - [j141]Filip Bjelonic, Joonho Lee, Philip Arm, Dhionis V. Sako, Davide Tateo, Jan Peters, Marco Hutter:
Learning-Based Design and Control for Quadrupedal Robots With Parallel-Elastic Actuators. IEEE Robotics Autom. Lett. 8(3): 1611-1618 (2023) - [j140]Siwei Ju, Peter van Vliet, Oleg Arenz, Jan Peters:
Digital Twin of a Driver-in-the-Loop Race Car Simulation With Contextual Reinforcement Learning. IEEE Robotics Autom. Lett. 8(7): 4107-4114 (2023) - [j139]Dieter Büchler, Roberto Calandra, Jan Peters:
Learning to Control Highly Accelerated Ballistic Movements on Muscular Robots. Robotics Auton. Syst. 159: 104230 (2023) - [j138]Andreas Look, Barbara Rakitsch, Melih Kandemir, Jan Peters:
Cheap and Deterministic Inference for Deep State-Space Models of Interacting Dynamical Systems. Trans. Mach. Learn. Res. 2023 (2023) - [j137]Stefan Löckel, Siwei Ju, Maximilian Schaller, Peter van Vliet, Jan Peters:
An Adaptive Human Driver Model for Realistic Race Car Simulations. IEEE Trans. Syst. Man Cybern. Syst. 53(11): 6718-6730 (2023) - [c272]Carlos E. Luis, Alessandro G. Bottero, Julia Vinogradska, Felix Berkenkamp, Jan Peters:
Model-Based Uncertainty in Value Functions. AISTATS 2023: 8029-8052 - [c271]Yaonan Zhu, Shukrullo Nazirjonov, Bingheng Jiang, Jacinto E. Colan Zaita, Tadayoshi Aoyama, Yasuhisa Hasegawa, Boris Belousov, Kay Hansel, Jan Peters:
Visual Tactile Sensor Based Force Estimation for Position-Force Teleoperation. CBS 2023: 49-52 - [c270]David Rother, Thomas H. Weisswange, Jan Peters:
Disentangling Interaction Using Maximum Entropy Reinforcement Learning in Multi-Agent Systems. ECAI 2023: 1994-2001 - [c269]Firas Al-Hafez, Davide Tateo, Oleg Arenz, Guoping Zhao, Jan Peters:
LS-IQ: Implicit Reward Regularization for Inverse Reinforcement Learning. ICLR 2023 - [c268]Daniel Palenicek, Michael Lutter, Joao Carvalho, Jan Peters:
Diminishing Return of Value Expansion Methods in Model-Based Reinforcement Learning. ICLR 2023 - [c267]Christoph Zelch, Jan Peters, Oskar von Stryk:
Start State Selection for Control Policy Learning from Optimal Trajectories. ICRA 2023: 3247-3253 - [c266]Julen Urain, Niklas Funk, Jan Peters, Georgia Chalvatzaki:
SE(3)-DiffusionFields: Learning smooth cost functions for joint grasp and motion optimization through diffusion. ICRA 2023: 5923-5930 - [c265]Puze Liu, Kuo Zhang, Davide Tateo, Snehal Jauhri, Zhiyuan Hu, Jan Peters, Georgia Chalvatzaki:
Safe Reinforcement Learning of Dynamic High-Dimensional Robotic Tasks: Navigation, Manipulation, Interaction. ICRA 2023: 9449-9456 - [c264]Kay Hansel, Julen Urain, Jan Peters, Georgia Chalvatzaki:
Hierarchical Policy Blending as Inference for Reactive Robot Control. ICRA 2023: 10181-10188 - [c263]An T. Le, Kay Hansel, Jan Peters, Georgia Chalvatzaki:
Hierarchical Policy Blending As Optimal Transport. L4DC 2023: 797-812 - [i171]Filip Bjelonic, Joonho Lee, Philip Arm, Dhionis V. Sako, Davide Tateo, Jan Peters, Marco Hutter:
Learning-based Design and Control for Quadrupedal Robots with Parallel-Elastic Actuators. CoRR abs/2301.03509 (2023) - [i170]Piotr Kicki, Puze Liu, Davide Tateo, Haitham Bou-Ammar, Krzysztof Walas, Piotr Skrzypczynski, Jan Peters:
Fast Kinodynamic Planning on the Constraint Manifold with Deep Neural Networks. CoRR abs/2301.04330 (2023) - [i169]Carlos E. Luis, Alessandro G. Bottero, Julia Vinogradska, Felix Berkenkamp, Jan Peters:
Model-Based Uncertainty in Value Functions. CoRR abs/2302.12526 (2023) - [i168]Shangding Gu, Alap Kshirsagar, Yali Du, Guang Chen, Yaodong Yang, Jan Peters, Alois C. Knoll:
A Human-Centered Safe Robot Reinforcement Learning Framework with Interactive Behaviors. CoRR abs/2302.13137 (2023) - [i167]Firas Al-Hafez, Davide Tateo, Oleg Arenz, Guoping Zhao, Jan Peters:
LS-IQ: Implicit Reward Regularization for Inverse Reinforcement Learning. CoRR abs/2303.00599 (2023) - [i166]Daniel Palenicek, Michael Lutter, Joao Carvalho, Jan Peters:
Diminishing Return of Value Expansion Methods in Model-Based Reinforcement Learning. CoRR abs/2303.03955 (2023) - [i165]Johanna Bethge, Maik Pfefferkorn, Alexander Rose, Jan Peters, Rolf Findeisen:
Model Predictive Control with Gaussian-Process-Supported Dynamical Constraints for Autonomous Vehicles. CoRR abs/2303.04725 (2023) - [i164]Andreas Look, Melih Kandemir, Barbara Rakitsch, Jan Peters:
Cheap and Deterministic Inference for Deep State-Space Models of Interacting Dynamical Systems. CoRR abs/2305.01773 (2023) - [i163]Jihao Andreas Lin, Joe Watson, Pascal Klink, Jan Peters:
Function-Space Regularization for Deep Bayesian Classification. CoRR abs/2307.06055 (2023) - [i162]João Carvalho, An T. Le, Mark Baierl, Dorothea Koert, Jan Peters:
Motion Planning Diffusion: Learning and Planning of Robot Motions with Diffusion Models. CoRR abs/2308.01557 (2023) - [i161]Carlos E. Luis, Alessandro G. Bottero, Julia Vinogradska, Felix Berkenkamp, Jan Peters:
Value-Distributional Model-Based Reinforcement Learning. CoRR abs/2308.06590 (2023) - [i160]Andreas Look, Melih Kandemir, Barbara Rakitsch, Jan Peters:
Sampling-Free Probabilistic Deep State-Space Models. CoRR abs/2309.08256 (2023) - [i159]Pascal Klink, Carlo D'Eramo, Jan Peters, Joni Pajarinen:
On the Benefit of Optimal Transport for Curriculum Reinforcement Learning. CoRR abs/2309.14091 (2023) - [i158]Pascal Klink, Florian Wolf, Kai Ploeger, Jan Peters, Joni Pajarinen:
Tracking Control for a Spherical Pendulum via Curriculum Reinforcement Learning. CoRR abs/2309.14096 (2023) - [i157]Hamish Flynn, David Reeb, Melih Kandemir, Jan Peters:
Improved Algorithms for Stochastic Linear Bandits Using Tail Bounds for Martingale Mixtures. CoRR abs/2309.14298 (2023) - [i156]An T. Le, Georgia Chalvatzaki, Armin Biess, Jan Peters:
Accelerating Motion Planning via Optimal Transport. CoRR abs/2309.15970 (2023) - [i155]Aryaman Reddi, Maximilian Tölle, Jan Peters, Georgia Chalvatzaki, Carlo D'Eramo:
Robust Adversarial Reinforcement Learning via Bounded Rationality Curricula. CoRR abs/2311.01642 (2023) - [i154]Gabriele Tiboni, Pascal Klink, Jan Peters, Tatiana Tommasi, Carlo D'Eramo, Georgia Chalvatzaki:
Domain Randomization via Entropy Maximization. CoRR abs/2311.01885 (2023) - [i153]Firas Al-Hafez, Guoping Zhao, Jan Peters, Davide Tateo:
LocoMuJoCo: A Comprehensive Imitation Learning Benchmark for Locomotion. CoRR abs/2311.02496 (2023) - [i152]Firas Al-Hafez, Guoping Zhao, Jan Peters, Davide Tateo:
Time-Efficient Reinforcement Learning with Stochastic Stateful Policies. CoRR abs/2311.04082 (2023) - [i151]Luca Lach, Robert Haschke, Davide Tateo, Jan Peters, Helge J. Ritter, Júlia Borràs Sol, Carme Torras:
Towards Transferring Tactile-based Continuous Force Control Policies from Simulation to Robot. CoRR abs/2311.07245 (2023) - [i150]Ahmed Hendawy, Jan Peters, Carlo D'Eramo:
Multi-Task Reinforcement Learning with Mixture of Orthogonal Experts. CoRR abs/2311.11385 (2023) - 2022
- [j136]Simone Parisi, Davide Tateo, Maximilian Hensel, Carlo D'Eramo, Jan Peters, Joni Pajarinen:
Long-Term Visitation Value for Deep Exploration in Sparse-Reward Reinforcement Learning. Algorithms 15(3): 81 (2022) - [j135]Hamish Flynn, David Reeb, Melih Kandemir, Jan Peters:
PAC-Bayesian lifelong learning for multi-armed bandits. Data Min. Knowl. Discov. 36(2): 841-876 (2022) - [j134]Fabio Muratore, Fabio Ramos, Greg Turk, Wenhao Yu, Michael Gienger, Jan Peters:
Robot Learning From Randomized Simulations: A Review. Frontiers Robotics AI 9: 799893 (2022) - [j133]Bang You, Oleg Arenz, Youping Chen, Jan Peters:
Integrating contrastive learning with dynamic models for reinforcement learning from images. Neurocomputing 476: 102-114 (2022) - [j132]Vignesh Prasad, Ruth Stock-Homburg, Jan Peters:
Human-Robot Handshaking: A Review. Int. J. Soc. Robotics 14(1): 277-293 (2022) - [j131]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:
HEBO: An Empirical Study of Assumptions in Bayesian Optimisation. J. Artif. Intell. Res. 74: 1269-1349 (2022) - [j130]Janosch Moos, Kay Hansel, Hany Abdulsamad, Svenja Stark, Debora Clever, Jan Peters:
Robust Reinforcement Learning: A Review of Foundations and Recent Advances. Mach. Learn. Knowl. Extr. 4(1): 276-315 (2022) - [j129]Samuele Tosatto, João Carvalho, Jan Peters:
Batch Reinforcement Learning With a Nonparametric Off-Policy Policy Gradient. IEEE Trans. Pattern Anal. Mach. Intell. 44(10): 5996-6010 (2022) - [j128]Riad Akrour, Davide Tateo, Jan Peters:
Continuous Action Reinforcement Learning From a Mixture of Interpretable Experts. IEEE Trans. Pattern Anal. Mach. Intell. 44(10): 6795-6806 (2022) - [j127]Niklas Funk, Charles B. Schaff, Rishabh Madan, Takuma Yoneda, Julen Urain De Jesus, Joe Watson, Ethan K. Gordon, Felix Widmaier, Stefan Bauer, Siddhartha S. Srinivasa, Tapomayukh Bhattacharjee, Matthew R. Walter, Jan Peters:
Benchmarking Structured Policies and Policy Optimization for Real-World Dexterous Object Manipulation. IEEE Robotics Autom. Lett. 7(1): 478-485 (2022) - [j126]Snehal Jauhri, Jan Peters, Georgia Chalvatzaki:
Robot Learning of Mobile Manipulation With Reachability Behavior Priors. IEEE Robotics Autom. Lett. 7(3): 8399-8406 (2022) - [j125]Tuan Dam, Georgia Chalvatzaki, Jan Peters, Joni Pajarinen:
Monte-Carlo Robot Path Planning. IEEE Robotics Autom. Lett. 7(4): 11213-11220 (2022) - [j124]Julen Urain, Davide Tateo, Jan Peters:
Learning Stable Vector Fields on Lie Groups. IEEE Robotics Autom. Lett. 7(4): 12569-12576 (2022) - [j123]Yi Zheng, Filipe Veiga, Jan Peters, Veronica J. Santos:
Autonomous Learning of Page Flipping Movements via Tactile Feedback. IEEE Trans. Robotics 38(5): 2734-2749 (2022) - [j122]Dieter Büchler, Simon Guist, Roberto Calandra, Vincent Berenz, Bernhard Schölkopf, Jan Peters:
Learning to Play Table Tennis From Scratch Using Muscular Robots. IEEE Trans. Robotics 38(6): 3850-3860 (2022) - [c262]Marius Memmel, Puze Liu, Davide Tateo, Jan Peters:
Dimensionality Reduction and Prioritized Exploration for Policy Search. AISTATS 2022: 2134-2157 - [c261]Joe Watson, Jan Peters:
Inferring Smooth Control: Monte Carlo Posterior Policy Iteration with Gaussian Processes. CoRL 2022: 67-79 - [c260]Jonathan Vorndamme, João Carvalho, Riddhiman Laha, Dorothea Koert, Luis Figueredo, Jan Peters, Sami Haddadin:
Integrated Bi-Manual Motion Generation and Control shaped for Probabilistic Movement Primitives. Humanoids 2022: 202-209 - [c259]João Carvalho, Dorothea Koert, Marek Daniv, Jan Peters:
Adapting Object-Centric Probabilistic Movement Primitives with Residual Reinforcement Learning. Humanoids 2022: 405-412 - [c258]Vignesh Prasad, Dorothea Koert, Ruth Stock-Homburg, Jan Peters, Georgia Chalvatzaki:
MILD: Multimodal Interactive Latent Dynamics for Learning Human-Robot Interaction. Humanoids 2022: 472-479 - [c257]Rustam Galljamov, Guoping Zhao, Boris Belousov, André Seyfarth, Jan Peters:
Improving Sample Efficiency of Example-Guided Deep Reinforcement Learning for Bipedal Walking. Humanoids 2022: 587-593 - [c256]Pascal Klink, Carlo D'Eramo, Jan Peters, Joni Pajarinen:
Boosted Curriculum Reinforcement Learning. ICLR 2022 - [c255]Pascal Klink, Haoyi Yang, Carlo D'Eramo, Jan Peters, Joni Pajarinen:
Curriculum Reinforcement Learning via Constrained Optimal Transport. ICML 2022: 11341-11358 - [c254]Kai Ploeger, Jan Peters:
Controlling the Cascade: Kinematic Planning for N-ball Toss Juggling. IROS 2022: 1139-1144 - [c253]Puze Liu, Kuo Zhang, Davide Tateo, Snehal Jauhri, Jan Peters, Georgia Chalvatzaki:
Regularized Deep Signed Distance Fields for Reactive Motion Generation. IROS 2022: 6673-6680 - [c252]Julen Urain, An T. Le, Alexander Lambert, Georgia Chalvatzaki, Byron Boots, Jan Peters:
Learning Implicit Priors for Motion Optimization. IROS 2022: 7672-7679 - [c251]Tim Schneider, Boris Belousov, Georgia Chalvatzaki, Diego Romeres, Devesh K. Jha, Jan Peters:
Active Exploration for Robotic Manipulation. IROS 2022: 9355-9362 - [c250]Niklas Funk, Svenja Menzenbach, Georgia Chalvatzaki, Jan Peters:
Graph-based Reinforcement Learning meets Mixed Integer Programs: An application to 3D robot assembly discovery. IROS 2022: 10215-10222 - [c249]Alessandro G. Bottero, Carlos E. Luis, Julia Vinogradska, Felix Berkenkamp, Jan Peters:
Information-Theoretic Safe Exploration with Gaussian Processes. NeurIPS 2022 - [c248]Ioannis Asmanis, Panagiotis Mermigkas, Georgia Chalvatzaki, Jan Peters, Petros Maragos:
A Semantic Enhancement of Unified Geometric Representations for Improving Indoor Visual SLAM. UR 2022: 288-294 - [i149]Tianyu Ren, Alexander Imani Cowen-Rivers, Haitham Bou-Ammar, Jan Peters:
Learning Geometric Constraints in Task and Motion Planning. CoRR abs/2201.09612 (2022) - [i148]Tuan Dam, Carlo D'Eramo, Jan Peters, Joni Pajarinen:
A Unified Perspective on Value Backup and Exploration in Monte-Carlo Tree Search. CoRR abs/2202.07071 (2022) - [i147]Bang You, Oleg Arenz, Youping Chen, Jan Peters:
Integrating Contrastive Learning with Dynamic Models for Reinforcement Learning from Images. CoRR abs/2203.01810 (2022) - [i146]Stefan Löckel, Siwei Ju, Maximilian Schaller, Peter van Vliet, Jan Peters:
An Adaptive Human Driver Model for Realistic Race Car Simulations. CoRR abs/2203.01909 (2022) - [i145]Hamish Flynn, David Reeb, Melih Kandemir, Jan Peters:
PAC-Bayesian Lifelong Learning For Multi-Armed Bandits. CoRR abs/2203.03303 (2022) - [i144]João Carvalho, Jan Peters:
An Analysis of Measure-Valued Derivatives for Policy Gradients. CoRR abs/2203.03917 (2022) - [i143]João Carvalho, Dorothea Koert, Marek Daniv, Jan Peters:
Residual Robot Learning for Object-Centric Probabilistic Movement Primitives. CoRR abs/2203.03918 (2022) - [i142]Jascha Hellwig, Mark Baierl, João Carvalho, Julen Urain, Jan Peters:
A Hierarchical Approach to Active Pose Estimation. CoRR abs/2203.03919 (2022) - [i141]Snehal Jauhri, Jan Peters, Georgia Chalvatzaki:
Robot Learning of Mobile Manipulation with Reachability Behavior Priors. CoRR abs/2203.04051 (2022) - [i140]Niklas Funk, Svenja Menzenbach, Georgia Chalvatzaki, Jan Peters:
Graph-based Reinforcement Learning meets Mixed Integer Programs: An application to 3D robot assembly discovery. CoRR abs/2203.04120 (2022) - [i139]Puze Liu, Kuo Zhang, Davide Tateo, Snehal Jauhri, Jan Peters, Georgia Chalvatzaki:
Regularized Deep Signed Distance Fields for Reactive Motion Generation. CoRR abs/2203.04739 (2022) - [i138]Marius Memmel, Puze Liu, Davide Tateo, Jan Peters:
Dimensionality Reduction and Prioritized Exploration for Policy Search. CoRR abs/2203.04791 (2022) - [i137]Lei Xu, Tianyu Ren, Georgia Chalvatzaki, Jan Peters:
Accelerating Integrated Task and Motion Planning with Neural Feasibility Checking. CoRR abs/2203.10568 (2022) - [i136]Daniel Palenicek, Michael Lutter, Jan Peters:
Revisiting Model-based Value Expansion. CoRR abs/2203.14660 (2022) - [i135]Alexander Lambert, An T. Le, Julen Urain, Georgia Chalvatzaki, Byron Boots, Jan Peters:
Learning Implicit Priors for Motion Optimization. CoRR abs/2204.05369 (2022) - [i134]Tim Schneider, Boris Belousov, Hany Abdulsamad, Jan Peters:
Active Inference for Robotic Manipulation. CoRR abs/2206.10313 (2022) - [i133]Kai Ploeger, Jan Peters:
Controlling the Cascade: Kinematic Planning for N-ball Toss Juggling. CoRR abs/2207.01414 (2022) - [i132]Tuan Dam, Georgia Chalvatzaki, Jan Peters, Joni Pajarinen:
Monte-Carlo Robot Path Planning. CoRR abs/2208.02673 (2022) - [i131]Julen Urain, Niklas Funk, Jan Peters, Georgia Chalvatzaki:
SE(3)-DiffusionFields: Learning smooth cost functions for joint grasp and motion optimization through diffusion. CoRR abs/2209.03855 (2022) - [i130]Alexander I. Cowen-Rivers, Philip John Gorinski, Aivar Sootla, Asif Khan, Furui Liu, Jun Wang, Jan Peters, Haitham Bou-Ammar:
Structured Q-learning For Antibody Design. CoRR abs/2209.04698 (2022) - [i129]Bang You, Jingming Xie, Youping Chen, Jan Peters, Oleg Arenz:
Self-supervised Sequential Information Bottleneck for Robust Exploration in Deep Reinforcement Learning. CoRR abs/2209.05333 (2022) - [i128]Puze Liu, Kuo Zhang, Davide Tateo, Snehal Jauhri, Zhiyuan Hu, Jan Peters, Georgia Chalvatzaki:
Safe reinforcement learning of dynamic high-dimensional robotic tasks: navigation, manipulation, interaction. CoRR abs/2209.13308 (2022) - [i127]Luca Lach, Niklas Funk, Robert Haschke, Séverin Lemaignan, Helge Joachim Ritter, Jan Peters, Georgia Chalvatzaki:
Placing by Touching: An empirical study on the importance of tactile sensing for precise object placing. CoRR abs/2210.02054 (2022) - [i126]Joe Watson, Jan Peters:
Inferring Smooth Control: Monte Carlo Posterior Policy Iteration with Gaussian Processes. CoRR abs/2210.03512 (2022) - [i125]Kay Hansel, Julen Urain, Jan Peters, Georgia Chalvatzaki:
Hierarchical Policy Blending as Inference for Reactive Robot Control. CoRR abs/2210.07890 (2022) - [i124]Vignesh Prasad, Dorothea Koert, Ruth Stock-Homburg, Jan Peters, Georgia Chalvatzaki:
MILD: Multimodal Interactive Latent Dynamics for Learning Human-Robot Interaction. CoRR abs/2210.12418 (2022) - [i123]Tim Schneider, Boris Belousov, Georgia Chalvatzaki, Diego Romeres, Devesh K. Jha, Jan Peters:
Active Exploration for Robotic Manipulation. CoRR abs/2210.12806 (2022) - [i122]Hany Abdulsamad, Peter Nickl, Pascal Klink, Jan Peters:
Variational Hierarchical Mixtures for Learning Probabilistic Inverse Dynamics. CoRR abs/2211.01120 (2022) - [i121]Max Siebenborn, Boris Belousov, Junning Huang, Jan Peters:
How Crucial is Transformer in Decision Transformer? CoRR abs/2211.14655 (2022) - [i120]Hamish Flynn, David Reeb, Melih Kandemir, Jan Peters:
PAC-Bayes Bounds for Bandit Problems: A Survey and Experimental Comparison. CoRR abs/2211.16110 (2022) - [i119]An T. Le, Kay Hansel, Jan Peters, Georgia Chalvatzaki:
Hierarchical Policy Blending As Optimal Transport. CoRR abs/2212.01938 (2022) - [i118]Alessandro G. Bottero, Carlos E. Luis, Julia Vinogradska, Felix Berkenkamp, Jan Peters:
Information-Theoretic Safe Exploration with Gaussian Processes. CoRR abs/2212.04914 (2022) - [i117]Yaonan Zhu, Shukrullo Nazirjonov, Bingheng Jiang, Jacinto E. Colan Zaita, Tadayoshi Aoyama, Yasuhisa Hasegawa, Boris Belousov, Kay Hansel, Jan Peters:
Visual Tactile Sensor Based Force Estimation for Position-Force Teleoperation. CoRR abs/2212.13007 (2022) - 2021
- [j121]Niyati Rawal, Dorothea Koert, Cigdem Turan, Kristian Kersting, Jan Peters, Ruth Stock-Homburg:
ExGenNet: Learning to Generate Robotic Facial Expression Using Facial Expression Recognition. Frontiers Robotics AI 8: 730317 (2021) - [j120]Carlo D'Eramo, Davide Tateo, Andrea Bonarini, Marcello Restelli, Jan Peters:
MushroomRL: Simplifying Reinforcement Learning Research. J. Mach. Learn. Res. 22: 131:1-131:5 (2021) - [j119]Pascal Klink, Hany Abdulsamad, Boris Belousov, Carlo D'Eramo, Jan Peters, Joni Pajarinen:
A Probabilistic Interpretation of Self-Paced Learning with Applications to Reinforcement Learning. J. Mach. Learn. Res. 22: 182:1-182:52 (2021) - [j118]Carlo D'Eramo, Andrea Cini, Alessandro Nuara, Matteo Pirotta, Cesare Alippi, Jan Peters, Marcello Restelli:
Gaussian Approximation for Bias Reduction in Q-Learning. J. Mach. Learn. Res. 22: 277:1-277:51 (2021) - [j117]Riad Akrour, Asma Atamna, Jan Peters:
Convex optimization with an interpolation-based projection and its application to deep learning. Mach. Learn. 110(8): 2267-2289 (2021) - [j116]Fabio Muratore, Michael Gienger, Jan Peters:
Assessing Transferability From Simulation to Reality for Reinforcement Learning. IEEE Trans. Pattern Anal. Mach. Intell. 43(4): 1172-1183 (2021) - [j115]