| Deep learning, reinforcement learning, and world models Y Matsuo, Y LeCun, M Sahani, D Precup, D Silver, M Sugiyama, E Uchibe, ... Neural Networks 152, 267-275, 2022 | 658 | 2022 |
| Learning from demonstration and adaptation of biped locomotion J Nakanishi, J Morimoto, G Endo, G Cheng, S Schaal, M Kawato Robotics and autonomous systems 47 (2-3), 79-91, 2004 | 567 | 2004 |
| Task-specific generalization of discrete and periodic dynamic movement primitives A Ude, A Gams, T Asfour, J Morimoto IEEE Transactions on Robotics 26 (5), 800-815, 2010 | 498 | 2010 |
| Acquisition of stand-up behavior by a real robot using hierarchical reinforcement learning J Morimoto, K Doya Robotics and Autonomous Systems 36 (1), 37-51, 2001 | 398 | 2001 |
| Robust reinforcement learning J Morimoto, K Doya Neural computation 17 (2), 335-359, 2005 | 370 | 2005 |
| A small number of abnormal brain connections predicts adult autism spectrum disorder N Yahata, J Morimoto, R Hashimoto, G Lisi, K Shibata, Y Kawakubo, ... Nature communications 7 (1), 11254, 2016 | 349 | 2016 |
| Learning CPG-based biped locomotion with a policy gradient method: Application to a humanoid robot G Endo, J Morimoto, T Matsubara, J Nakanishi, G Cheng The International Journal of Robotics Research 27 (2), 213-228, 2008 | 299 | 2008 |
| CB: A humanoid research platform for exploring neuroscience G Cheng, SH Hyon, J Morimoto, A Ude, JG Hale, G Colvin, W Scroggin, ... Advanced Robotics 21 (10), 1097-1114, 2007 | 298 | 2007 |
| Orientation in cartesian space dynamic movement primitives A Ude, B Nemec, T Petrić, J Morimoto 2014 IEEE International Conference on Robotics and Automation (ICRA), 2997-3004, 2014 | 286 | 2014 |
| Harmonization of resting-state functional MRI data across multiple imaging sites via the separation of site differences into sampling bias and measurement bias A Yamashita, N Yahata, T Itahashi, G Lisi, T Yamada, N Ichikawa, ... PLoS biology 17 (4), e3000042, 2019 | 230 | 2019 |
| Bilinear modeling of EMG signals to extract user-independent features for multiuser myoelectric interface T Matsubara, J Morimoto IEEE Transactions on Biomedical Engineering 60 (8), 2205-2213, 2013 | 229 | 2013 |
| Experimental studies of a neural oscillator for biped locomotion with QRIO G Endo, J Nakanishi, J Morimoto, G Cheng Proceedings of the 2005 IEEE international conference on robotics and …, 2005 | 210 | 2005 |
| Robot and attitude control method of robot G Endo, M Kawato, G Cheng, J Nakanishi, J Morimoto US Patent 7,657,345, 2010 | 200 | 2010 |
| Adaptive control of exoskeleton robots for periodic assistive behaviours based on EMG feedback minimisation L Peternel, T Noda, T Petrič, A Ude, J Morimoto, J Babič PloS one 11 (2), e0148942, 2016 | 195 | 2016 |
| A multi-site, multi-disorder resting-state magnetic resonance image database SC Tanaka, A Yamashita, N Yahata, T Itahashi, G Lisi, T Yamada, ... Scientific data 8 (1), 227, 2021 | 177 | 2021 |
| EMG-based model predictive control for physical human–robot interaction: Application for assist-as-needed control T Teramae, T Noda, J Morimoto IEEE Robotics and Automation Letters 3 (1), 210-217, 2017 | 173 | 2017 |
| An empirical exploration of a neural oscillator for biped locomotion control G Endo, J Morimoto, J Nakanishi, G Cheng IEEE International Conference on Robotics and Automation, 2004. Proceedings …, 2004 | 171 | 2004 |
| Minimax differential dynamic programming: Application to a biped walking robot J Morimioto, G Zeglin, CG Atkeson SICE 2003 Annual Conference (IEEE Cat. No. 03TH8734) 3, 2310-2315, 2003 | 169 | 2003 |
| A biologically inspired biped locomotion strategy for humanoid robots: Modulation of sinusoidal patterns by a coupled oscillator model J Morimoto, G Endo, J Nakanishi, G Cheng IEEE Transactions on Robotics 24 (1), 185-191, 2008 | 158 | 2008 |
| Learning CPG-based biped locomotion with a policy gradient method T Matsubara, J Morimoto, J Nakanishi, M Sato, K Doya Robotics and Autonomous Systems 54 (11), 911-920, 2006 | 158 | 2006 |
Gordon ChengTechnical University of MunichVerified email at tum.de
