| Conformal prediction: A gentle introduction AN Angelopoulos, S Bates Foundations and Trends in Machine Learning 16 (4), 494-591, 2023 | 1674* | 2023 |
| Cross-validation: what does it estimate and how well does it do it? S Bates, T Hastie, R Tibshirani Journal of the American Statistical Association, 1-22, 2023 | 589 | 2023 |
| Uncertainty sets for image classifiers using conformal prediction A Angelopoulos*, S Bates*, J Malik, MI Jordan International Conference on Learning Representations, 2021 | 541 | 2021 |
| Distribution-free, risk-controlling prediction sets S Bates*, A Angelopoulos*, L Lei*, J Malik, MI Jordan Journal of the ACM 68 (6), 2021 | 296 | 2021 |
| Prediction-powered inference AN Angelopoulos*, S Bates*, C Fannjiang*, MI Jordan*, T Zrnic* Science 382 (6671), 669-674, 2023 | 275 | 2023 |
| Conformal risk control AN Angelopoulos*, S Bates*, A Fisch*, L Lei*, T Schuster* International Conference on Learning Representations, 2024 | 265 | 2024 |
| Testing for outliers with conformal p-values S Bates*, E Candès*, L Lei*, Y Romano*, M Sesia* Annals of Statistics 51 (1), 149-178, 2023 | 240 | 2023 |
| Learn then test: Calibrating predictive algorithms to achieve risk control AN Angelopoulos*, S Bates*, EJ Candès*, MI Jordan*, L Lei* Annals of Applied Statistics, 2025 | 198 | 2025 |
| Image-to-image regression with distribution-free uncertainty quantification and applications in imaging AN Angelopoulos, AP Kohli, S Bates, M Jordan, J Malik, T Alshaabi, ... International Conference on Machine Learning, 717-730, 2022 | 139 | 2022 |
| Conformal prediction under feedback covariate shift for biomolecular design C Fannjiang, S Bates, AN Angelopoulos, J Listgarten, MI Jordan Proceedings of the National Academy of Sciences 119 (43), e2204569119, 2022 | 119* | 2022 |
| Class-conditional conformal prediction with many classes T Ding, A Angelopoulos, S Bates, M Jordan, RJ Tibshirani Advances in neural information processing systems 36, 64555-64576, 2023 | 117 | 2023 |
| False discovery rate control in genome-wide association studies with population structure M Sesia, S Bates, E Candès, J Marchini, C Sabatti Proceedings of the National Academy of Sciences 118 (40), e2105841118, 2021 | 115* | 2021 |
| Theoretical foundations of conformal prediction AN Angelopoulos*, RF Barber*, S Bates* arXiv preprint arXiv:2411.11824, 2024 | 113 | 2024 |
| Metropolized knockoff sampling S Bates*, E Candès*, L Janson*, W Wang* Journal of the American Statistical Association 116 (535), 1413-1427, 2021 | 111 | 2021 |
| Multi-resolution localization of causal variants across the genome M Sesia, E Katsevich, S Bates, E Candès, C Sabatti Nature communications 11 (1), 1093, 2020 | 110 | 2020 |
| The sample complexity of online contract design B Zhu, S Bates, Z Yang, Y Wang, J Jiao, MI Jordan Proceedings of the 24th ACM Conference on Economics and Computation, 2023 | 90 | 2023 |
| Causal inference in genetic trio studies S Bates, M Sesia, C Sabatti, E Candès Proceedings of the National Academy of Sciences 117 (39), 24117-24126, 2020 | 76 | 2020 |
| Achieving Equalized Odds by Resampling Sensitive Attributes Y Romano, S Bates, EJ Candès Advances in Neural Information Processing Systems (NeurIPS), 2020 | 74 | 2020 |
| Achieving risk control in online learning settings S Feldman, L Ringel, S Bates, Y Romano Transactions on Machine Learning Research, 2023 | 66* | 2023 |
| Improving conditional coverage via orthogonal quantile regression S Feldman, S Bates, Y Romano Advances in neural information processing systems 34, 2060-2071, 2021 | 62 | 2021 |
Anastasios Nikolas AngelopoulosPh.D. Student, UC BerkeleyVerified email at berkeley.edu
