| Robust reinforcement learning: A review of foundations and recent advances J Moos, K Hansel, H Abdulsamad, S Stark, D Clever, J Peters Machine Learning and Knowledge Extraction 4 (1), 276-315, 2022 | 149 | 2022 |
| Self-paced contextual reinforcement learning P Klink, H Abdulsamad, B Belousov, J Peters Conference on Robot Learning, 513-529, 2020 | 56 | 2020 |
| Model-free trajectory optimization for reinforcement learning R Akrour, G Neumann, H Abdulsamad, A Abdolmaleki International Conference on Machine Learning, 2961-2970, 2016 | 54 | 2016 |
| Stochastic optimal control as approximate input inference J Watson, H Abdulsamad, J Peters Conference on Robot Learning, 697-716, 2020 | 39 | 2020 |
| Model-free trajectory-based policy optimization with monotonic improvement R Akrour, A Abdolmaleki, H Abdulsamad, J Peters, G Neumann Journal of machine learning research 19 (14), 1-25, 2018 | 32 | 2018 |
| Reinforcement learning algorithms: analysis and applications B Belousov, H Abdulsamad, P Klink, S Parisi, J Peters Springer, 2021 | 29 | 2021 |
| A probabilistic interpretation of self-paced learning with applications to reinforcement learning P Klink, H Abdulsamad, B Belousov, C D'Eramo, J Peters, J Pajarinen Journal of Machine Learning Research 22 (182), 1-52, 2021 | 28 | 2021 |
| Receding horizon curiosity M Schultheis, B Belousov, H Abdulsamad, J Peters Conference on robot learning, 1278-1288, 2020 | 25 | 2020 |
| Reinforcement learning vs human programming in tetherball robot games S Parisi, H Abdulsamad, A Paraschos, C Daniel, J Peters 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2015 | 20 | 2015 |
| A nonparametric off-policy policy gradient S Tosatto, J Carvalho, H Abdulsamad, J Peters International Conference on Artificial Intelligence and Statistics, 167-177, 2020 | 16 | 2020 |
| Efficient stochastic optimal control through approximate Bayesian input inference J Watson, H Abdulsamad, R Findeisen, J Peters arXiv preprint arXiv:2105.07693, 2021 | 11* | 2021 |
| Hierarchical decomposition of nonlinear dynamics and control for system identification and policy distillation H Abdulsamad, J Peters Learning for Dynamics and Control, 904-914, 2020 | 11 | 2020 |
| Active inference for robotic manipulation T Schneider, B Belousov, H Abdulsamad, J Peters arXiv preprint arXiv:2206.10313, 2022 | 10 | 2022 |
| Chance-constrained trajectory optimization for non-linear systems with unknown stochastic dynamics O Celik, H Abdulsamad, J Peters 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2019 | 10 | 2019 |
| Optimal control and inverse optimal control by distribution matching O Arenz, H Abdulsamad, G Neumann 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2016 | 8 | 2016 |
| A variational infinite mixture for probabilistic inverse dynamics learning H Abdulsamad, P Nickl, P Klink, J Peters 2021 IEEE International Conference on Robotics and Automation (ICRA), 4216-4222, 2021 | 5 | 2021 |
| Reinforcement learning algorithms B Belousov, H Abdulsamad, P Klink, S Parisi, J Peters Analysis and applications 883, 2021 | 5 | 2021 |
| State-regularized policy search for linearized dynamical systems H Abdulsamad, O Arenz, J Peters, G Neumann Proceedings of the International Conference on Automated Planning and …, 2017 | 5 | 2017 |
| Model-based reinforcement learning via stochastic hybrid models H Abdulsamad, J Peters IEEE Open Journal of Control Systems 2, 155-170, 2023 | 4 | 2023 |
| Distributionally Robust Trajectory Optimization Under Uncertain Dynamics via Relative Entropy Trust-Regions H Abdulsamad, T Dorau, B Belousov, JJ Zhu, J Peters arXiv preprint arXiv:2103.15388, 2021 | 4 | 2021 |
Jan PetersProfessor for Intelligent Autonomous Systems/TU Darmstadt, Dept. Head/German AI Research Center DFKIVerified email at ias.tu-darmstadt.de