Stephen Bates
Stephen Bates
Assistant Professor, MIT EECS
Verified email at - Homepage
Cited by
Cited by
Conformal prediction: A gentle introduction
AN Angelopoulos, S Bates
Foundations and TrendsŪ in Machine Learning 16 (4), 494-591, 2023
Uncertainty sets for image classifiers using conformal prediction
A Angelopoulos*, S Bates*, J Malik, MI Jordan
International Conference on Learning Representations, 2021
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
Distribution-free, risk-controlling prediction sets
S Bates*, A Angelopoulos*, L Lei*, J Malik, MI Jordan
Journal of the ACM 68 (6), 2021
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
Learn then test: Calibrating predictive algorithms to achieve risk control
AN Angelopoulos, S Bates, EJ Candès, MI Jordan, L Lei
arXiv preprint arXiv:2110.01052, 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
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
Metropolized knockoff sampling
S Bates, E Candès, L Janson, W Wang
Journal of the American Statistical Association 116 (535), 1413-1427, 2021
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
Conformal risk control
AN Angelopoulos, S Bates, A Fisch, L Lei, T Schuster
arXiv preprint arXiv:2208.02814, 2022
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
Prediction-powered inference
AN Angelopoulos, S Bates, C Fannjiang, MI Jordan, T Zrnic
Science 382 (6671), 669-674, 2023
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
Achieving Equalized Odds by Resampling Sensitive Attributes
Y Romano, S Bates, EJ Candès
Advances in Neural Information Processing Systems (NeurIPS), 2020
Log-ratio lasso: scalable, sparse estimation for log-ratio models
S Bates, R Tibshirani
Biometrics 75 (2), 613-624, 2019
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
Robust Calibration with Multi-domain Temperature Scaling
Y Yu, S Bates, Y Ma, MI Jordan
Advances in Neural Information Processing Systems (NeurIPS), 2022
Improving conditional coverage via orthogonal quantile regression
S Feldman, S Bates, Y Romano
Advances in neural information processing systems 34, 2060-2071, 2021
Achieving risk control in online learning settings
S Feldman, L Ringel, S Bates, Y Romano
Transactions on Machine Learning Research, 2023
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