| Learning the signatures of the human grasp using a scalable tactile glove S Sundaram, P Kellnhofer, Y Li, JY Zhu, A Torralba, W Matusik Nature 569 (7758), 698-702, 2019 | 445 | 2019 |
| InfoGAIL: Interpretable Imitation Learning from Visual Demonstrations Y Li, J Song, S Ermon Advances in Neural Information Processing Systems (NIPS), 2017 | 350* | 2017 |
| Clevrer: Collision events for video representation and reasoning K Yi, C Gan, Y Li, P Kohli, J Wu, A Torralba, JB Tenenbaum International Conference on Learning Representations (ICLR), 2020 | 201 | 2020 |
| Learning particle dynamics for manipulating rigid bodies, deformable objects, and fluids Y Li, J Wu, R Tedrake, JB Tenenbaum, A Torralba International Conference on Learning Representations (ICLR), 2019 | 181 | 2019 |
| Face Detection with End-to-End Integration of a ConvNet and a 3D Model Y Li, B Sun, T Wu, Y Wang European Conference on Computer Vision (ECCV), 420-436, 2016 | 152 | 2016 |
| Propagation Networks for Model-Based Control Under Partial Observation Y Li, J Wu, JY Zhu, JB Tenenbaum, A Torralba, R Tedrake International Conference on Robotics and Automation (ICRA), 2019 | 79 | 2019 |
| Connecting Touch and Vision via Cross-Modal Prediction Y Li, JY Zhu, R Tedrake, A Torralba Computer Vision and Pattern Recognition (CVPR), 2019 | 60 | 2019 |
| Learning human–environment interactions using conformal tactile textiles Y Luo, Y Li, P Sharma, W Shou, K Wu, M Foshey, B Li, T Palacios, ... Nature Electronics 4 (3), 193-201, 2021 | 57 | 2021 |
| Learning Compositional Koopman Operators for Model-Based Control Y Li, H He, J Wu, D Katabi, A Torralba International Conference on Learning Representations (ICLR), 2020 | 55 | 2020 |
| Causal discovery in physical systems from videos Y Li, A Torralba, A Anandkumar, D Fox, A Garg Neural Information Processing Systems (NeurIPS), 2020 | 45 | 2020 |
| Keypoints into the Future: Self-Supervised Correspondence in Model-Based Reinforcement Learning L Manuelli, Y Li, P Florence, R Tedrake Conference on Robot Learning (CoRL), 2020 | 43 | 2020 |
| Learning physical graph representations from visual scenes DM Bear, C Fan, D Mrowca, Y Li, S Alter, A Nayebi, J Schwartz, L Fei-Fei, ... Neural Information Processing Systems (NeurIPS), 2020 | 43 | 2020 |
| Skin Cancer Detection and Tracking using Data Synthesis and Deep Learning Y Li, A Esteva, B Kuprel, R Novoa, J Ko, S Thrun Workshops at the Thirty-First AAAI Conference on Artificial Intelligence, 2017 | 35 | 2017 |
| Visual Grounding of Learned Physical Models Y Li, T Lin, K Yi, D Bear, DLK Yamins, J Wu, JB Tenenbaum, A Torralba International Conference on Machine Learning (ICML), 2020 | 32 | 2020 |
| 3D Neural Scene Representations for Visuomotor Control Y Li, S Li, V Sitzmann, P Agrawal, A Torralba Conference on Robot Learning (CoRL), 2021 | 17 | 2021 |
| Intelligent carpet: Inferring 3d human pose from tactile signals Y Luo, Y Li, M Foshey, W Shou, P Sharma, T Palacios, A Torralba, ... Computer Vision and Pattern Recognition (CVPR), 2021 | 9 | 2021 |
| DiffSkill: Skill Abstraction from Differentiable Physics for Deformable Object Manipulations with Tools X Lin, Z Huang, Y Li, JB Tenenbaum, D Held, C Gan International Conference on Learning Representations (ICLR), 2022 | 6 | 2022 |
| Learning multi-object dynamics with compositional neural radiance fields D Driess, Z Huang, Y Li, R Tedrake, M Toussaint arXiv preprint arXiv:2202.11855, 2022 | 5 | 2022 |
| ComPhy: Compositional Physical Reasoning of Objects and Events from Videos Z Chen, K Yi, Y Li, M Ding, A Torralba, JB Tenenbaum, C Gan International Conference on Learning Representations (ICLR), 2022 | 4 | 2022 |
| RoboCraft: Learning to See, Simulate, and Shape Elasto-Plastic Objects with Graph Networks H Shi, H Xu, Z Huang, Y Li, J Wu Robotics: Science and Systems (RSS), 2022 | 1 | 2022 |
Antonio TorralbaProfessor of Computer Science, MITEmail confirmado em csail.mit.edu
