| Habitat 2.0: Training home assistants to rearrange their habitat A Szot, A Clegg, E Undersander, E Wijmans, Y Zhao, J Turner, N Maestre, ... Advances in neural information processing systems 34, 251-266, 2021 | 405 | 2021 |
| Adversarial continual learning S Ebrahimi, F Meier, R Calandra, T Darrell, M Rohrbach Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 204 | 2020 |
| Generalized inner loop meta-learning E Grefenstette, B Amos, D Yarats, PM Htut, A Molchanov, F Meier, D Kiela, ... arXiv preprint arXiv:1910.01727, 2019 | 163 | 2019 |
| On the use of simulation in robotics: Opportunities, challenges, and suggestions for moving forward HS Choi, C Crump, C Duriez, A Elmquist, G Hager, D Han, F Hearl, ... Proceedings of the National Academy of Sciences 118 (1), e1907856118, 2021 | 140 | 2021 |
| Meta learning via learned loss S Bechtle, A Molchanov, Y Chebotar, E Grefenstette, L Righetti, ... 2020 25th International Conference on Pattern Recognition (ICPR), 4161-4168, 2021 | 111 | 2021 |
| Movement segmentation using a primitive library F Meier, E Theodorou, F Stulp, S Schaal 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2011 | 105 | 2011 |
| Real-time perception meets reactive motion generation D Kappler, F Meier, J Issac, J Mainprice, CG Cifuentes, M Wüthrich, ... IEEE Robotics and Automation Letters 3 (3), 1864-1871, 2018 | 99 | 2018 |
| 3D shape context and distance transform for action recognition M Grundmann, F Meier, I Essa 2008 19th International Conference on Pattern Recognition, 1-4, 2008 | 97 | 2008 |
| From dynamic movement primitives to associative skill memories P Pastor, M Kalakrishnan, F Meier, F Stulp, J Buchli, E Theodorou, ... Robotics and Autonomous Systems 61 (4), 351-361, 2013 | 94 | 2013 |
| Se3-pose-nets: Structured deep dynamics models for visuomotor control A Byravan, F Leeb, F Meier, D Fox 2018 IEEE International Conference on Robotics and Automation (ICRA), 3339-3346, 2018 | 92* | 2018 |
| Where are we in the search for an artificial visual cortex for embodied intelligence? A Majumdar, K Yadav, S Arnaud, J Ma, C Chen, S Silwal, A Jain, ... Advances in Neural Information Processing Systems 36, 2024 | 77 | 2024 |
| Model-based inverse reinforcement learning from visual demonstrations N Das, S Bechtle, T Davchev, D Jayaraman, A Rai, F Meier Conference on Robot Learning, 1930-1942, 2021 | 68 | 2021 |
| Incremental local gaussian regression F Meier, P Hennig, S Schaal Advances in Neural Information Processing Systems 27, 2014 | 68 | 2014 |
| Learning coupling terms for obstacle avoidance A Rai, F Meier, A Ijspeert, S Schaal 2014 IEEE-RAS international conference on humanoid robots, 512-518, 2014 | 59 | 2014 |
| Encoding physical constraints in differentiable newton-euler algorithm G Sutanto, A Wang, Y Lin, M Mukadam, G Sukhatme, A Rai, F Meier Learning for Dynamics and Control, 804-813, 2020 | 56 | 2020 |
| Residual learning from demonstration: Adapting dmps for contact-rich manipulation T Davchev, KS Luck, M Burke, F Meier, S Schaal, S Ramamoorthy IEEE Robotics and Automation Letters 7 (2), 4488-4495, 2022 | 53 | 2022 |
| Learning generalizable locomotion skills with hierarchical reinforcement learning T Li, N Lambert, R Calandra, F Meier, A Rai 2020 IEEE International Conference on Robotics and Automation (ICRA), 413-419, 2020 | 47 | 2020 |
| Learning feedback terms for reactive planning and control A Rai, G Sutanto, S Schaal, F Meier 2017 IEEE International Conference on Robotics and Automation (ICRA), 2184-2191, 2017 | 46 | 2017 |
| Using simulation to improve sample-efficiency of Bayesian optimization for bipedal robots A Rai, R Antonova, F Meier, CG Atkeson Journal of machine learning research 20 (49), 1-24, 2019 | 45 | 2019 |
| Towards robust online inverse dynamics learning F Meier, D Kappler, N Ratliff, S Schaal 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2016 | 45 | 2016 |
Stefan SchaalRobotics, Machine Learning, AI, Neuroscience在 google.com 的电子邮件经过验证
