Making sense of vision and touch: Self-supervised learning of multimodal representations for contact-rich tasks MA Lee, Y Zhu, K Srinivasan, P Shah, S Savarese, L Fei-Fei, A Garg, ... 2019 International Conference on Robotics and Automation (ICRA), 8943-8950, 2019 | 359 | 2019 |
Variable impedance control in end-effector space: An action space for reinforcement learning in contact-rich tasks R Martín-Martín, MA Lee, R Gardner, S Savarese, J Bohg, A Garg 2019 IEEE/RSJ international conference on intelligent robots and systems …, 2019 | 190 | 2019 |
Making sense of vision and touch: Learning multimodal representations for contact-rich tasks MA Lee, Y Zhu, P Zachares, M Tan, K Srinivasan, S Savarese, L Fei-Fei, ... IEEE Transactions on Robotics 36 (3), 582-596, 2020 | 179 | 2020 |
Multibench: Multiscale benchmarks for multimodal representation learning PP Liang, Y Lyu, X Fan, Z Wu, Y Cheng, J Wu, L Chen, P Wu, MA Lee, ... arXiv preprint arXiv:2107.07502, 2021 | 105 | 2021 |
Anemia in rural China's elementary schools: prevalence and correlates in Shaanxi province's poor counties R Luo, M Kleiman-Weiner, S Rozelle, L Zhang, C Liu, B Sharbono, Y Shi, ... Ecology of food and nutrition 49 (5), 357-372, 2010 | 56 | 2010 |
Guided uncertainty-aware policy optimization: Combining learning and model-based strategies for sample-efficient policy learning MA Lee, C Florensa, J Tremblay, N Ratliff, A Garg, F Ramos, D Fox 2020 IEEE International Conference on Robotics and Automation (ICRA), 7505-7512, 2020 | 54 | 2020 |
Multimodal sensor fusion with differentiable filters MA Lee, B Yi, R Martín-Martín, S Savarese, J Bohg 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2020 | 50 | 2020 |
On the opportunities and risks of foundation models (2021) R Bommasani, DA Hudson, E Adeli, R Altman, S Arora, S von Arx, ... arXiv preprint arXiv:2108.07258, 2022 | 34 | 2022 |
& Liang, P.(2021). On the opportunities and risks of foundation models R Bommasani, DA Hudson, E Adeli, R Altman, S Arora, S von Arx, ... arXiv preprint arXiv:2108.07258, 0 | 33 | |
Detect, reject, correct: Crossmodal compensation of corrupted sensors MA Lee, M Tan, Y Zhu, J Bohg 2021 IEEE international conference on robotics and automation (ICRA), 909-916, 2021 | 23 | 2021 |
Differentiable factor graph optimization for learning smoothers B Yi, MA Lee, A Kloss, R Martín-Martín, J Bohg 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2021 | 22 | 2021 |
See, hear, and feel: Smart sensory fusion for robotic manipulation H Li, Y Zhang, J Zhu, S Wang, MA Lee, H Xu, E Adelson, L Fei-Fei, R Gao, ... arXiv preprint arXiv:2212.03858, 2022 | 21 | 2022 |
Interpreting contact interactions to overcome failure in robot assembly tasks PA Zachares, MA Lee, W Lian, J Bohg 2021 IEEE International Conference on Robotics and Automation (ICRA), 3410-3417, 2021 | 17 | 2021 |
On the Opportunities and Risks of Foundation Models. arXiv [cs. LG], 2021 R Bommasani, DA Hudson, E Adeli, R Altman, S Arora, S von Arx, ... | 10 | |
Guided uncertainty-aware policy optimization: combining model-free and model-based strategies for sample-efficient learning J Tremblay, D Fox, M Lee, C Florensa, ND Ratliff, G Animesh, FT Ramos US Patent App. 16/780,465, 2021 | 7 | 2021 |
Fusion for Robot Perception and Control MA Lee Stanford University, 2021 | | 2021 |
See, Hear, and Feel: Smart Sensory Fusion for Robotic Manipulation (Supplementary Materials) H Li, Y Zhang, J Zhu, S Wang, MA Lee, H Xu, E Adelson, L Fei-Fei, R Gao, ... | | |