RMA: Rapid motor adaptation for legged robots A Kumar, Z Fu, D Pathak, J Malik Robotics: Science and Systems, 2021 | 387 | 2021 |
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 | 207 | 2019 |
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 | 140 | 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 | 134 | 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 | 91 | 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 | 84 | 2021 |
Mobile ALOHA: Learning bimanual mobile manipulation with low-cost whole-body teleoperation Z Fu, TZ Zhao, C Finn arXiv preprint arXiv:2401.02117, 2024 | 81 | 2024 |
Robot parkour learning Z Zhuang, Z Fu, J Wang, C Atkeson, S Schwertfeger, C Finn, H Zhao Conference on Robot Learning, 2023 | 67 | 2023 |
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 | 50 | 2022 |
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 | 23 | 2019 |
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 | 23 | 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 | 19 | 2020 |
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 | 17 | 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 | 8 | 2020 |
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 | 3 | 2023 |
Adversarial attack against scene recognition system for unmanned vehicles X Wang, M Wen, J Li, Z Fu, R Lu, K Chen Proceedings of the ACM Turing Celebration Conference-China, 1-6, 2019 | 2 | 2019 |
HumanPlus: Humanoid Shadowing and Imitation from Humans Z Fu, Q Zhao, Q Wu, G Wetzstein, C Finn arXiv preprint arXiv:2406.10454, 2024 | 1 | 2024 |
Multi-Modal Imitation Learning in Partially Observable Environments Z Fu, M Liu, M Zhou, W Zhang | 1 | 2020 |