| Deep orientation uncertainty learning based on a bingham loss I Gilitschenski, R Sahoo, W Schwarting, A Amini, S Karaman, D Rus International conference on learning representations, 2019 | 77 | 2019 |
| Calibrating predictions to decisions: A novel approach to multi-class calibration S Zhao, M Kim, R Sahoo, T Ma, S Ermon Advances in Neural Information Processing Systems 34, 22313-22324, 2021 | 73 | 2021 |
| Reliable decisions with threshold calibration R Sahoo, S Zhao, A Chen, S Ermon Advances in Neural Information Processing Systems 34, 1831-1844, 2021 | 34 | 2021 |
| Learning from a biased sample R Sahoo, L Lei, S Wager arXiv preprint arXiv:2209.01754, 2022 | 24 | 2022 |
| Unsupervised domain adaptation in the absence of source data R Sahoo, D Shanmugam, J Guttag arXiv preprint arXiv:2007.10233, 2020 | 23 | 2020 |
| Policy learning under biased sample selection L Lei, R Sahoo, S Wager arXiv preprint arXiv:2304.11735, 2023 | 17 | 2023 |
| Policy learning with competing agents R Sahoo, S Wager arXiv preprint arXiv:2204.01884, 2022 | 12 | 2022 |
| Tree Covers: An Alternative to Metric Embeddings R Sahoo, I Chami, C Ré Differential Geometry for Machine Learning Workshop at NeurIPS, 2020 | 2 | 2020 |
