| RMA: Rapid motor adaptation for legged robots A Kumar, Z Fu, D Pathak, J Malik Robotics: Science and Systems, 2021 | 536 | 2021 |
| Open X-Embodiment: Robotic learning datasets and RT-X models A Padalkar, A Pooley, A Jain, A Bewley, A Herzog, A Irpan, A Khazatsky, ... International Conference on Robotics and Automation, 2023 | 469* | 2023 |
| Energy theft detection with energy privacy preservation in the smart grid D Yao, M Wen, X Liang, Z Fu, K Zhang, B Yang IEEE Internet of Things Journal 6 (5), 7659-7669, 2019 | 239 | 2019 |
| Mobile ALOHA: Learning Bimanual Mobile Manipulation with Low-Cost Whole-Body Teleoperation Z Fu, TZ Zhao, C Finn Conference on Robot Learning, 2024 | 223 | 2024 |
| Machine learning for glass science and engineering: A review H Liu, Z Fu, K Yang, X Xu, M Bauchy Journal of Non-Crystalline Solids 557, 119419, 2021 | 151 | 2021 |
| Robot parkour learning Z Zhuang, Z Fu, J Wang, C Atkeson, S Schwertfeger, C Finn, H Zhao Conference on Robot Learning, 2023 | 149 | 2023 |
| Deep whole-body control: learning a unified policy for manipulation and locomotion Z Fu, X Cheng, D Pathak Conference on Robot Learning, 138-149, 2022 | 144 | 2022 |
| Minimizing energy consumption leads to the emergence of gaits in legged robots Z Fu, A Kumar, J Malik, D Pathak Conference on Robot Learning, 2021 | 124 | 2021 |
| Coupling vision and proprioception for navigation of legged robots Z Fu, A Kumar, A Agarwal, H Qi, J Malik, D Pathak Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 72 | 2022 |
| HumanPlus: Humanoid Shadowing and Imitation from Humans Z Fu, Q Zhao, Q Wu, G Wetzstein, C Finn Conference on Robot Learning, 2024 | 44 | 2024 |
| Parameterization of empirical forcefields for glassy silica using machine learning H Liu, Z Fu, Y Li, NFA Sabri, M Bauchy MRS Communications 9 (2), 593-599, 2019 | 27 | 2019 |
| Balance between accuracy and simplicity in empirical forcefields for glass modeling: insights from machine learning H Liu, Z Fu, Y Li, NFA Sabri, M Bauchy Journal of Non-Crystalline Solids 515, 133-142, 2019 | 26 | 2019 |
| Emergence of pragmatics from referential game between theory of mind agents L Yuan, Z Fu, J Shen, L Xu, J Shen, SC Zhu NeurIPS 2019 Emergent Communication Workshop, 2020 | 23 | 2020 |
| UMI on Legs: Making manipulation policies mobile with manipulation-centric whole-body controllers H Ha, Y Gao, Z Fu, J Tan, S Song Conference on Robot Learning, 2024 | 21 | 2024 |
| Exploring the landscape of Buckingham potentials for silica by machine learning: Soft vs hard interatomic forcefields H Liu, Y Li, Z Fu, K Li, M Bauchy The Journal of Chemical Physics 152 (5), 2020 | 20 | 2020 |
| Machine learning forcefield for silicate glasses H Liu, Z Fu, Y Li, NFA Sabri, M Bauchy arXiv preprint arXiv:1902.03486, 2019 | 15 | 2019 |
| Emergence of Theory of Mind Collaboration in Multiagent Systems L Yuan, Z Fu, L Zhou, K Yang, SC Zhu NeurIPS 2019 Emergent Communication Workshop, 2020 | 13 | 2020 |
| Mobility VLA: Multimodal instruction navigation with long-context VLMs and topological graphs HTL Chiang, Z Xu, Z Fu, MG Jacob, T Zhang, TWE Lee, W Yu, C Schenck, ... Conference on Robot Learning, 2024 | 10 | 2024 |
| Reducing overestimation in value mixing for cooperative deep multi-agent reinforcement learning Z Fu, Q Zhao, W Zhang Proceedings of the international conference on agents and artificial …, 2020 | 7 | 2020 |
| Adapt On-the-Go: Behavior Modulation for Single-Life Robot Deployment AS Chen, G Chada, L Smith, A Sharma, Z Fu, S Levine, C Finn arXiv preprint arXiv:2311.01059, 2023 | 6 | 2023 |
Deepak PathakAssistant Professor, Carnegie Mellon University確認したメール アドレス: cs.cmu.edu