| Data-efficient Domain Randomization with Bayesian Optimization F Muratore, C Eilers, M Gienger, J Peters IEEE Robotics and Automation Letters, 2021 | 87* | 2021 |
| Robot learning from randomized simulations: A review F Muratore, F Ramos, G Turk, W Yu, M Gienger, J Peters Frontiers in Robotics and AI 9, 799893, 2022 | 73 | 2022 |
| Assessing Transferability from Simulation to Reality for Reinforcement Learning F Muratore, M Gienger, J Peters IEEE Transactions on Pattern Analysis and Machine Intelligence, 2019 | 68 | 2019 |
| Domain randomization for simulation-based policy optimization with transferability assessment F Muratore, F Treede, M Gienger, J Peters Conference on Robot Learning, 700-713, 2018 | 63 | 2018 |
| Neural posterior domain randomization F Muratore, T Gruner, F Wiese, B Belousov, M Gienger, J Peters Conference on Robot Learning, 1532-1542, 2022 | 31 | 2022 |
| Simurlacra-a framework for reinforcement learning from randomized simulations F Muratore | 9 | 2020 |
| An Empirical Analysis of Measure-Valued Derivatives for Policy Gradients J Carvalho, D Tateo, F Muratore, J Peters International Joint Conference on Neural Networks (IJCNN), 2021 | 6 | 2021 |
| Underactuated Waypoint Trajectory Optimization for Light Painting Photography C Eilers, J Eschmann, R Menzenbach, B Belousov, F Muratore, J Peters IEEE International Conference on Robotics and Automation, 1505-1510, 2020 | 5 | 2020 |
| Distilled domain randomization J Brosseit, B Hahner, F Muratore, M Gienger, J Peters arXiv preprint arXiv:2112.03149, 2021 | 4 | 2021 |
| Randomizing Physics Simulations for Robot Learning F Muratore Technische Universität Darmstadt, 2021 | 2 | 2021 |
| An Approach for Modelling the Structural Dynamics of a Mechanical System based on a Takagi-Sugeno Representation SJ Pieczona, F Muratore, MF Zaeh Conference on Competitive Manufacturing, 391-398, 2016 | 2 | 2016 |
| Assessing Transferability in Reinforcement Learning from Randomized Simulations F Muratore, M Gienger, J Peters Reinforcement Learning and Decision Making (RLDM), 2019 | 1 | 2019 |
| Pseudo-likelihood inference T Gruner, B Belousov, F Muratore, D Palenicek, JR Peters Advances in Neural Information Processing Systems 36, 2024 | | 2024 |
Jan PetersProfessor for Intelligent Autonomous Systems/TU Darmstadt, Dept. Head/German AI Research Center DFKI在 ias.tu-darmstadt.de 的电子邮件经过验证
