| Machine learning in a data-limited regime: Augmenting experiments with synthetic data uncovers order in crumpled sheets J Hoffmann, Y Bar-Sinai, LM Lee, J Andrejevic, S Mishra, SM Rubinstein, ... Science advances 5 (4), eaau6792, 2019 | 78 | 2019 |
| On multi-objective policy optimization as a tool for reinforcement learning A Abdolmaleki, SH Huang, G Vezzani, B Shahriari, JT Springenberg, ... arXiv preprint arXiv:2106.08199, 2021 | 24 | 2021 |
| Augmenting learning using symmetry in a biologically-inspired domain S Mishra, A Abdolmaleki, A Guez, P Trochim, D Precup NewInML workshop, NeurIPS 2019 arXiv:1910.00528, 2019 | 10 | 2019 |
| Coordinated crawling via reinforcement learning S Mishra, WM van Rees, L Mahadevan Journal of the Royal Society Interface 17 (169), 20200198, 2020 | 6 | 2020 |
| Computing the viscous effect in early-time drop impact dynamics S Mishra, SM Rubinstein, CH Rycroft Journal of Fluid Mechanics 945, A13, 2022 | 5 | 2022 |
| Thermal design of the FETS chopper beam dump S Mishra, M Aslaninejad, P Savage, PA Posocco, JK Pozimski, ... PAC2013, Pasadena, 2013 | 3 | 2013 |
| Policy composition in reinforcement learning via multi-objective policy optimization S Mishra, A Anand, J Hoffmann, N Heess, M Riedmiller, A Abdolmaleki, ... LocoLearn workshop, CoRL 2024 arXiv preprint arXiv:2308.15470, 2023 | | 2023 |
| Simulating the evolution and control of dynamical systems S Mishra Harvard University, 2021 | | 2021 |