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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
- 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.uni-trier.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
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2020 – today
- 2021
[j114]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)- [j113]Fabio Muratore, Christian Eilers, Michael Gienger, Jan Peters:
Data-Efficient Domain Randomization With Bayesian Optimization. IEEE Robotics Autom. Lett. 6(2): 911-918 (2021) - [j112]Daniel Tanneberg, Kai Ploeger, Elmar Rueckert, Jan Peters:
SKID RAW: Skill Discovery From Raw Trajectories. IEEE Robotics Autom. Lett. 6(3): 4696-4703 (2021) - [j111]Sebastian Höfer, Kostas Bekris, Ankur Handa, Juan Camilo Gamboa, Melissa Mozifian, Florian Golemo, Christopher G. Atkeson, Dieter Fox, Ken Goldberg, John Leonard, C. Karen Liu, Jan Peters, Shuran Song, Peter Welinder, Martha White:
Sim2Real in Robotics and Automation: Applications and Challenges. IEEE Trans Autom. Sci. Eng. 18(2): 398-400 (2021) - [c226]Joe Watson, Jihao Andreas Lin, Pascal Klink, Joni Pajarinen, Jan Peters:
Latent Derivative Bayesian Last Layer Networks. AISTATS 2021: 1198-1206 - [i104]Vignesh Prasad, Ruth Stock-Homburg, Jan Peters:
Human-Robot Handshaking: A Review. CoRR abs/2102.07193 (2021) - [i103]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. CoRR abs/2102.13176 (2021) - [i102]Vignesh Prasad, Ruth Stock-Homburg, Jan Peters:
Learning Human-like Hand Reaching for Human-Robot Handshaking. CoRR abs/2103.00616 (2021) - [i101]Tianyu Ren, Georgia Chalvatzaki, Jan Peters:
Extended Task and Motion Planning of Long-horizon Robot Manipulation. CoRR abs/2103.05456 (2021) - [i100]Joe Watson, Jan Peters:
Advancing Trajectory Optimization with Approximate Inference: Exploration, Covariance Control and Adaptive Risk. CoRR abs/2103.06319 (2021) - [i99]Andrew S. Morgan, Daljeet Nandha, Georgia Chalvatzaki, Carlo D'Eramo, Aaron M. Dollar, Jan Peters:
Model Predictive Actor-Critic: Accelerating Robot Skill Acquisition with Deep Reinforcement Learning. CoRR abs/2103.13842 (2021) - [i98]Daniel Tanneberg, Kai Ploeger, Elmar Rueckert, Jan Peters:
SKID RAW: Skill Discovery from Raw Trajectories. CoRR abs/2103.14610 (2021) - [i97]Hany Abdulsamad, Tim Dorau, Boris Belousov, Jia-Jie Zhu, Jan Peters:
Distributionally Robust Trajectory Optimization Under Uncertain Dynamics via Relative-Entropy Trust Regions. CoRR abs/2103.15388 (2021) - [i96]Stephan Weigand, Pascal Klink, Jan Peters, Joni Pajarinen:
Reinforcement Learning using Guided Observability. CoRR abs/2104.10986 (2021) - [i95]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. CoRR abs/2105.02087 (2021) - [i94]Michael Lutter, Shie Mannor, Jan Peters, Dieter Fox, Animesh Garg:
Value Iteration in Continuous Actions, States and Time. CoRR abs/2105.04682 (2021) - [i93]Julen Urain, Anqi Li, Puze Liu, Carlo D'Eramo, Jan Peters:
Composable Energy Policies for Reactive Motion Generation and Reinforcement Learning. CoRR abs/2105.04962 (2021) - [i92]Joe Watson, Hany Abdulsamad, Rolf Findeisen, Jan Peters:
Stochastic Control through Approximate Bayesian Input Inference. CoRR abs/2105.07693 (2021) - [i91]Daniel Tanneberg, Elmar Rueckert, Jan Peters:
Evolutionary Training and Abstraction Yields Algorithmic Generalization of Neural Computers. CoRR abs/2105.07957 (2021) - [i90]Michael Lutter, Shie Mannor, Jan Peters, Dieter Fox, Animesh Garg:
Robust Value Iteration for Continuous Control Tasks. CoRR abs/2105.12189 (2021) - 2020
- [j110]Mikko Lauri, Joni Pajarinen, Jan Peters:
Multi-agent active information gathering in discrete and continuous-state decentralized POMDPs by policy graph improvement. Auton. Agents Multi Agent Syst. 34(2): 42 (2020) - [j109]Marco Ewerton, Oleg Arenz, Jan Peters:
Assisted teleoperation in changing environments with a mixture of virtual guides. Adv. Robotics 34(18): 1157-1170 (2020) - [j108]Dorothea Koert, Maximilian Kircher, Vildan Salikutluk, Carlo D'Eramo, Jan Peters:
Multi-Channel Interactive Reinforcement Learning for Sequential Tasks. Frontiers Robotics AI 7: 97 (2020) - [j107]Filipe Veiga, Riad Akrour, Jan Peters:
Hierarchical Tactile-Based Control Decomposition of Dexterous In-Hand Manipulation Tasks. Frontiers Robotics AI 7: 521448 (2020) - [j106]Dorothea Koert, Susanne Trick, Marco Ewerton, Michael Lutter, Jan Peters:
Incremental Learning of an Open-Ended Collaborative Skill Library. Int. J. Humanoid Robotics 17(1): 2050001:1-2050001:23 (2020) - [j105]Rudolf Lioutikov, Guilherme Maeda, Filipe Veiga, Kristian Kersting, Jan Peters:
Learning attribute grammars for movement primitive sequencing. Int. J. Robotics Res. 39(1) (2020) - [j104]Julia Vinogradska, Bastian Bischoff, Jan Achterhold, Torsten Koller, Jan Peters:
Numerical Quadrature for Probabilistic Policy Search. IEEE Trans. Pattern Anal. Mach. Intell. 42(1): 164-175 (2020) - [j103]Sebastián Gómez-González, Sergey Prokudin, Bernhard Schölkopf, Jan Peters:
Real Time Trajectory Prediction Using Deep Conditional Generative Models. IEEE Robotics Autom. Lett. 5(2): 970-976 (2020) - [j102]Stefan Löckel, Jan Peters, Peter van Vliet:
A Probabilistic Framework for Imitating Human Race Driver Behavior. IEEE Robotics Autom. Lett. 5(2): 2086-2093 (2020) - [j101]Kurena Motokura, Masaki Takahashi, Marco Ewerton, Jan Peters:
Plucking Motions for Tea Harvesting Robots Using Probabilistic Movement Primitives. IEEE Robotics Autom. Lett. 5(2): 3275-3282 (2020) - [j100]Mikko Lauri, Joni Pajarinen, Jan Peters, Simone Frintrop:
Multi-Sensor Next-Best-View Planning as Matroid-Constrained Submodular Maximization. IEEE Robotics Autom. Lett. 5(4): 5323-5330 (2020) - [j99]Joni Pajarinen, Oleg Arenz, Jan Peters, Gerhard Neumann:
Probabilistic Approach to Physical Object Disentangling. IEEE Robotics Autom. Lett. 5(4): 5510-5517 (2020) - [j98]Simon Manschitz, Michael Gienger, Jens Kober, Jan Peters:
Learning Sequential Force Interaction Skills. Robotics 9(2): 45 (2020) - [j97]Filipe Veiga, Benoni B. Edin, Jan Peters:
Grip Stabilization through Independent Finger Tactile Feedback Control. Sensors 20(6): 1748 (2020) - [j96]Sebastián Gómez-González, Gerhard Neumann, Bernhard Schölkopf, Jan Peters:
Adaptation and Robust Learning of Probabilistic Movement Primitives. IEEE Trans. Robotics 36(2): 366-379 (2020) - [c225]Samuele Tosatto, João Carvalho, Hany Abdulsamad, Jan Peters:
A Nonparametric Off-Policy Policy Gradient. AISTATS 2020: 167-177 - [c224]Ruth Stock-Homburg, Jan Peters, Katharina Schneider, Vignesh Prasad, Lejla Nukovic:
Evaluation of the Handshake Turing Test for anthropomorphic Robots. HRI (Companion) 2020: 456-458 - [c223]Carlo D'Eramo, Davide Tateo, Andrea Bonarini, Marcello Restelli, Jan Peters:
Sharing Knowledge in Multi-Task Deep Reinforcement Learning. ICLR 2020 - [c222]Christian Eilers, Jonas Eschmann, Robin Menzenbach, Boris Belousov, Fabio Muratore, Jan Peters:
Underactuated Waypoint Trajectory Optimization for Light Painting Photography. ICRA 2020: 1505-1510 - [c221]Christoph Zelch, Jan Peters, Oskar von Stryk:
Learning Control Policies from Optimal Trajectories. ICRA 2020: 2529-2535 - [c220]Tuan Dam, Pascal Klink, Carlo D'Eramo, Jan Peters, Joni Pajarinen:
Generalized Mean Estimation in Monte-Carlo Tree Search. IJCAI 2020: 2397-2404 - [c219]Julen Urain, Michele Ginesi, Davide Tateo, Jan Peters:
ImitationFlow: Learning Deep Stable Stochastic Dynamic Systems by Normalizing Flows. IROS 2020: 5231-5237 - [c218]Nils Rottmann, Tjasa Kunavar, Jan Babic, Jan Peters, Elmar Rueckert:
Learning Hierarchical Acquisition Functions for Bayesian Optimization. IROS 2020: 5490-5496 - [c217]Melvin Laux, Oleg Arenz, Jan Peters, Joni Pajarinen:
Deep Adversarial Reinforcement Learning for Object Disentangling. IROS 2020: 5504-5510 - [c216]Anton Ziese, Mario D. Fiore, Jan Peters, Uwe E. Zimmermann, Jürgen Adamy:
Redundancy resolution under hard joint constraints: a generalized approach to rank updates. IROS 2020: 7447-7453 - [c215]Leon Keller, Daniel Tanneberg, Svenja Stark, Jan Peters:
Model-Based Quality-Diversity Search for Efficient Robot Learning. IROS 2020: 9675-9680 - [c214]Allan Almeida Santos, Edwin Mora, Jan Peters, Florian Steinke:
Decentralized Data-Driven Tuning of Droop Frequency Controllers. ISGT-Europe 2020: 141-145 - [c213]Hany Abdulsamad, Jan Peters:
Hierarchical Decomposition of Nonlinear Dynamics and Control for System Identification and Policy Distillation. L4DC 2020: 904-914 - [c212]Pascal Klink, Carlo D'Eramo, Jan Peters, Joni Pajarinen:
Self-Paced Deep Reinforcement Learning. NeurIPS 2020 - [c211]Vignesh Prasad, Ruth Stock-Homburg, Jan Peters:
Advances in Human-Robot Handshaking. ICSR 2020: 478-489 - [c210]Diego Agudelo-España, Sebastián Gómez-González, Stefan Bauer, Bernhard Schölkopf, Jan Peters:
Bayesian Online Prediction of Change Points. UAI 2020: 320-329 - [i89]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. CoRR abs/2001.00119 (2020) - [i88]Carlo D'Eramo, Davide Tateo, Andrea Bonarini, Marcello Restelli, Jan Peters:
MushroomRL: Simplifying Reinforcement Learning Research. CoRR abs/2001.01102 (2020) - [i87]Samuele Tosatto, João Carvalho, Hany Abdulsamad, Jan Peters:
A Nonparametric Offpolicy Policy Gradient. CoRR abs/2001.02435 (2020) - [i86]Stefan Löckel, Jan Peters, Peter van Vliet:
A Probabilistic Framework for Imitating Human Race Driver Behavior. CoRR abs/2001.08255 (2020) - [i85]Ruth Stock-Homburg, Jan Peters, Katharina Schneider, Vignesh Prasad, Lejla Nukovic:
Evaluation of the Handshake Turing Test for anthropomorphic Robots. CoRR abs/2001.10464 (2020) - [i84]Samuele Tosatto, Riad Akrour, Jan Peters:
An Upper Bound of the Bias of Nadaraya-Watson Kernel Regression under Lipschitz Assumptions. CoRR abs/2001.10972 (2020) - [i83]Joni Pajarinen, Oleg Arenz, Jan Peters, Gerhard Neumann:
Probabilistic approach to physical object disentangling. CoRR abs/2002.11495 (2020) - [i82]Christian Eilers, Jonas Eschmann, Robin Menzenbach, Boris Belousov, Fabio Muratore, Jan Peters:
Underactuated Waypoint Trajectory Optimization for Light Painting Photography. CoRR abs/2003.01554 (2020) - [i81]Fabio Muratore, Christian Eilers, Michael Gienger, Jan Peters:
Bayesian Domain Randomization for Sim-to-Real Transfer. CoRR abs/2003.02471 (2020) - [i80]Samuele Tosatto, Jonas Stadtmueller, Jan Peters:
Dimensionality Reduction of Movement Primitives in Parameter Space. CoRR abs/2003.02634 (2020) - [i79]Marcus Ebner von Eschenbach, Binyamin Manela, Jan Peters, Armin Biess:
Metric-Based Imitation Learning Between Two Dissimilar Anthropomorphic Robotic Arms. CoRR abs/2003.02638 (2020) - [i78]Melvin Laux, Oleg Arenz, Jan Peters, Joni Pajarinen:
Deep Adversarial Reinforcement Learning for Object Disentangling. CoRR abs/2003.03779 (2020) - [i77]Philip Becker-Ehmck, Maximilian Karl, Jan Peters, Patrick van der Smagt:
Learning to Fly via Deep Model-Based Reinforcement Learning. CoRR abs/2003.08876 (2020) - [i76]Andrea Cini, Carlo D'Eramo, Jan Peters, Cesare Alippi:
Deep Reinforcement Learning with Weighted Q-Learning. CoRR abs/2003.09280 (2020) - [i75]Pascal Klink, Carlo D'Eramo, Jan Peters, Joni Pajarinen:
Self-Paced Deep Reinforcement Learning. CoRR abs/2004.11812 (2020) - [i74]Hany Abdulsamad, Jan Peters:
Hierarchical Decomposition of Nonlinear Dynamics and Control for System Identification and Policy Distillation. CoRR abs/2005.01432 (2020) - [i73]Nikolaos Gkanatsios, Georgia Chalvatzaki, Petros Maragos, Jan Peters:
Orientation Attentive Robot Grasp Synthesis. CoRR abs/2006.05123 (2020) - [i72]Riad Akrour, Davide Tateo, Jan Peters:
Reinforcement Learning from a Mixture of Interpretable Experts. CoRR abs/2006.05911 (2020) - [i71]Dieter Büchler, Simon Guist, Roberto Calandra, Vincent Berenz, Bernhard Schölkopf, Jan Peters:
Learning to Play Table Tennis From Scratch using Muscular Robots. CoRR abs/2006.05935 (2020) - [i70]Andreas Look, Chen Qiu, Maja R. Rudolph, Jan Peters, Melih Kandemir:
Deterministic Inference of Neural Stochastic Differential Equations. CoRR abs/2006.08973 (2020) - [i69]Tuan Dam, Carlo D'Eramo, Jan Peters, Joni Pajarinen:
Convex Regularization in Monte-Carlo Tree Search. CoRR abs/2007.00391 (2020) - [i68]Mikko Lauri, Joni Pajarinen, Jan Peters, Simone Frintrop:
Multi-Sensor Next-Best-View Planning as Matroid-Constrained Submodular Maximization. CoRR abs/2007.02084 (2020) - [i67]Leon Keller, Daniel Tanneberg, Svenja Stark, Jan Peters:
Model-Based Quality-Diversity Search for Efficient Robot Learning. CoRR abs/2008.04589 (2020) - [i66]Marco Ewerton, Oleg Arenz, Jan Peters:
Assisted Teleoperation in Changing Environments with a Mixture of Virtual Guides. CoRR abs/2008.05251 (2020) - [i65]Vignesh Prasad, Ruth Stock-Homburg, Jan Peters:
Advances in Human-Robot Handshaking. CoRR abs/2008.11695 (2020) - [i64]Joe Watson, Abraham Imohiosen, Jan Peters:
Active Inference or Control as Inference? A Unifying View. CoRR abs/2010.00262 (2020) - [i63]Andreas Look, Simona Doneva, Melih Kandemir, Rainer Gemulla, Jan Peters:
Differentiable Implicit Layers. CoRR abs/2010.07078 (2020) - [i62]Michael Lutter, Johannes Silberbauer, Joe Watson, Jan Peters:
A Differentiable Newton Euler Algorithm for Multi-body Model Learning. CoRR abs/2010.09802 (2020) - [i61]Julen Urain, Michele Ginesi, Davide Tateo, Jan Peters:
ImitationFlow: Learning Deep Stable Stochastic Dynamic Systems by Normalizing Flows. CoRR abs/2010.13129 (2020) - [i60]Kai Ploeger, Michael Lutter, Jan Peters:
High Acceleration Reinforcement Learning for Real-World Juggling with Binary Rewards. CoRR abs/2010.13483 (2020) - [i59]Samuele Tosatto, Georgia Chalvatzaki, Jan Peters:
Contextual Latent-Movements Off-Policy Optimization for Robotic Manipulation Skills. CoRR abs/2010.13766 (2020) - [i58]Samuele Tosatto, João Carvalho, Jan Peters:
Batch Reinforcement Learning with a Nonparametric Off-Policy Policy Gradient. CoRR abs/2010.14771 (2020) - [i57]Michael Lutter, Johannes Silberbauer, Joe Watson, Jan Peters:
Differentiable Physics Models for Real-world Offline Model-based Reinforcement Learning. CoRR abs/2011.01734 (2020) - [i56]Hany Abdulsamad, Peter Nickl, Pascal Klink, Jan Peters:
A Variational Infinite Mixture for Probabilistic Inverse Dynamics Learning. CoRR abs/2011.05217 (2020) - [i55]Riad Akrour, Asma Atamna, Jan Peters:
Convex Optimization with an Interpolation-based Projection and its Application to Deep Learning. CoRR abs/2011.07016 (2020) - [i54]Sebastian Höfer, Kostas Bekris, Ankur Handa, Juan Camilo Gamboa Higuera, Florian Golemo, Melissa Mozifian, Christopher G. Atkeson, Dieter Fox, Ken Goldberg, John Leonard, C. Karen Liu, Jan Peters, Shuran Song, Peter Welinder, Martha White:
Perspectives on Sim2Real Transfer for Robotics: A Summary of the R: SS 2020 Workshop. CoRR abs/2012.03806 (2020) - [i53]Julen Urain, Davide Tateo, Tianyu Ren, Jan Peters:
Structured Policy Representation: Imposing Stability in arbitrarily conditioned dynamic systems. CoRR abs/2012.06224 (2020)
2010 – 2019
- 2019
- [j95]Boris Belousov, Jan Peters:
Entropic Regularization of Markov Decision Processes. Entropy 21(7): 674 (2019) - [j94]Tim Schürmann, Betty J. Mohler, Jan Peters, Philipp Beckerle:
How Cognitive Models of Human Body Experience Might Push Robotics. Frontiers Neurorobotics 13: 14 (2019) - [j93]Marco Ewerton, Oleg Arenz, Guilherme Maeda, Dorothea Koert, Zlatko Kolev, Masaki Takahashi, Jan Peters:
Learning Trajectory Distributions for Assisted Teleoperation and Path Planning. Frontiers Robotics AI 6: 89 (2019) - [j92]Carlos Celemin, Guilherme Maeda, Javier Ruiz-del-Solar, Jan Peters, Jens Kober:
Reinforcement learning of motor skills using Policy Search and human corrective advice. Int. J. Robotics Res. 38(14) (2019) - [j91]Joni Pajarinen, Hong Linh Thai, Riad Akrour, Jan Peters, Gerhard Neumann:
Compatible natural gradient policy search. Mach. Learn. 108(8-9): 1443-1466 (2019) - [j90]Simone Parisi, Voot Tangkaratt, Jan Peters, Mohammad Emtiyaz Khan:
TD-regularized actor-critic methods. Mach. Learn. 108(8-9): 1467-1501 (2019) - [j89]Daniel Tanneberg, Jan Peters, Elmar Rueckert:
Intrinsic motivation and mental replay enable efficient online adaptation in stochastic recurrent networks. Neural Networks 109: 67-80 (2019) - [j88]Okan Koc, Jan Peters:
Learning to Serve: An Experimental Study for a New Learning From Demonstrations Framework. IEEE Robotics Autom. Lett. 4(2): 1784-1791 (2019) - [j87]Florian Brandherm, Jan Peters, Gerhard Neumann, Riad Akrour:
Learning Replanning Policies With Direct Policy Search. IEEE Robotics Autom. Lett. 4(2): 2196-2203 (2019) - [j86]Dorothea Koert, Joni Pajarinen, Albert Schotschneider, Susanne Trick, Constantin A. Rothkopf, Jan Peters:
Learning Intention Aware Online Adaptation of Movement Primitives. IEEE Robotics Autom. Lett. 4(4): 3719-3726 (2019) - [j85]Sebastián Gómez-González, Yassine Nemmour, Bernhard Schölkopf, Jan Peters:
Reliable Real-Time Ball Tracking for Robot Table Tennis. Robotics 8(4): 90 (2019) - [j84]Okan Koc, Guilherme Maeda, Jan Peters:
Optimizing the Execution of Dynamic Robot Movements With Learning Control. IEEE Trans. Robotics 35(4): 909-924 (2019) - [c209]Mikko Lauri, Joni Pajarinen, Jan Peters:
Information Gathering in Decentralized POMDPs by Policy Graph Improvement. AAMAS 2019: 1143-1151 - [c208]Pascal Klink, Hany Abdulsamad, Boris Belousov, Jan Peters:
Self-Paced Contextual Reinforcement Learning. CoRL 2019: 513-529 - [c207]Michael Lutter, Boris Belousov, Kim Listmann, Debora Clever, Jan Peters:
HJB Optimal Feedback Control with Deep Differential Value Functions and Action Constraints. CoRL 2019: 640-650 - [c206]Joe Watson, Hany Abdulsamad, Jan Peters:
Stochastic Optimal Control as Approximate Input Inference. CoRL 2019: 697-716 - [c205]Matthias Schultheis, Boris Belousov, Hany Abdulsamad, Jan Peters:
Receding Horizon Curiosity. CoRL 2019: 1278-1288 - [c204]Boris Belousov, Alymbek Sadybakasov, Bastian Wibranek, Filipe Veiga, Oliver Tessmann, Jan Peters:
Building a Library of Tactile Skills Based on FingerVision. Humanoids 2019: 717-722 - [c203]Michael Lutter, Christian Ritter, Jan Peters:
Deep Lagrangian Networks: Using Physics as Model Prior for Deep Learning. ICLR (Poster) 2019 - [c202]Riad Akrour, Joni Pajarinen, Jan Peters, Gerhard Neumann:
Projections for Approximate Policy Iteration Algorithms. ICML 2019: 181-190 - [c201]Philip Becker-Ehmck, Jan Peters, Patrick van der Smagt:
Switching Linear Dynamics for Variational Bayes Filtering. ICML 2019: 553-562 - [c200]Samuele Tosatto, Carlo D'Eramo, Joni Pajarinen, Marcello Restelli, Jan Peters:
Exploration Driven by an Optimistic Bellman Equation. IJCNN 2019: 1-8 - [c199]David Nass, Boris Belousov, Jan Peters:
Entropic Risk Measure in Policy Search. IROS 2019: 1101-1106 - [c198]Svenja Stark, Jan Peters, Elmar Rueckert:
Experience Reuse with Probabilistic Movement Primitives. IROS 2019: 1210-1217 - [c197]Julen Urain, Jan Peters:
Generalized Multiple Correlation Coefficient as a Similarity Measurement between Trajectories. IROS 2019: 1363-1369 - [c196]Marco Ewerton, Guilherme Maeda, Dorothea Koert, Zlatko Kolev, Masaki Takahashi, Jan Peters:
Reinforcement Learning of Trajectory Distributions: Applications in Assisted Teleoperation and Motion Planning. IROS 2019: 4294-4300 - [c195]Zinan Liu, Arne Hitzmann, Shuhei Ikemoto, Svenja Stark, Jan Peters, Koh Hosoda:
Local Online Motor Babbling: Learning Motor Abundance of a Musculoskeletal Robot Arm*. IROS 2019: 6594-6601 - [c194]Onur Celik, Hany Abdulsamad, Jan Peters:
Chance-Constrained Trajectory Optimization for Non-linear Systems with Unknown Stochastic Dynamics. IROS 2019: 6828-6833 - [c193]Susanne Trick, Dorothea Koert, Jan Peters, Constantin A. Rothkopf:
Multimodal Uncertainty Reduction for Intention Recognition in Human-Robot Interaction. IROS 2019: 7009-7016 - [c192]Michael Lutter, Kim Listmann, Jan Peters:
Deep Lagrangian Networks for end-to-end learning of energy-based control for under-actuated systems. IROS 2019: 7718-7725 - [c191]Ozan Özdenizci, Timm Meyer, Felix A. Wichmann, Jan Peters, Bernhard Schölkopf, Müjdat Çetin, Moritz Grosse-Wentrup:
Neural Signatures of Motor Skill in the Resting Brain. SMC 2019: 4387-4394 - [i52]Paavo Parmas, Carl Edward Rasmussen, Jan Peters, Kenji Doya:
PIPPS: Flexible Model-Based Policy Search Robust to the Curse of Chaos. CoRR abs/1902.01240 (2019) - [i51]Joni Pajarinen, Hong Linh Thai, Riad Akrour, Jan Peters, Gerhard Neumann:
Compatible Natural Gradient Policy Search. CoRR abs/1902.02823 (2019) - [i50]Diego Agudelo-España, Sebastián Gómez-González, Stefan Bauer, Bernhard Schölkopf, Jan Peters:
Bayesian Online Detection and Prediction of Change Points. CoRR abs/1902.04524 (2019) - [i49]Mikko Lauri, Joni Pajarinen, Jan Peters:
Information Gathering in Decentralized POMDPs by Policy Graph Improvement. CoRR abs/1902.09840 (2019) - [i48]Kristian Kersting, Jan Peters, Constantin A. Rothkopf:
Was ist eine Professur fuer Kuenstliche Intelligenz? CoRR abs/1903.09516 (2019) - [i47]