Stephen Bates
Stephen Bates
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Uncertainty sets for image classifiers using conformal prediction
A Angelopoulos, S Bates, J Malik, MI Jordan
International Conference on Learning Representations (ICLR), 2021
Multi-resolution localization of causal variants across the genome
M Sesia, E Katsevich, S Bates, E Candès, C Sabatti
Nature communications 11 (1), 1-10, 2020
Distribution-free, risk-controlling prediction sets
S Bates, A Angelopoulos, L Lei, J Malik, MI Jordan
Journal of the ACM 68 (6), 2021
Cross-validation: what does it estimate and how well does it do it?
S Bates, T Hastie, R Tibshirani
arXiv preprint arXiv:2104.00673, 2021
A gentle introduction to conformal prediction and distribution-free uncertainty quantification
AN Angelopoulos, S Bates
arXiv preprint arXiv:2107.07511, 2021
Metropolized knockoff sampling
S Bates, E Candès, L Janson, W Wang
Journal of the American Statistical Association 116 (535), 1413-1427, 2021
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
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
Testing for outliers with conformal p-values
S Bates, E Candès, L Lei, Y Romano, M Sesia
arXiv preprint arXiv:2104.08279, 2021
Log‐ratio lasso: scalable, sparse estimation for log‐ratio models
S Bates, R Tibshirani
Biometrics 75 (2), 613-624, 2019
Achieving Equalized Odds by Resampling Sensitive Attributes
Y Romano, S Bates, EJ Candès
Advances in Neural Information Processing Systems (NeurIPS), 2020
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
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 prediction for the design problem
C Fannjiang, S Bates, A Angelopoulos, J Listgarten, MI Jordan
arXiv preprint arXiv:2202.03613, 2022
Improving conditional coverage via orthogonal quantile regression
S Feldman, S Bates, Y Romano
Advances in Neural Information Processing Systems 34, 2060-2071, 2021
Calibrated multiple-output quantile regression with representation learning
S Feldman, S Bates, Y Romano
arXiv preprint arXiv:2110.00816, 2021
Private prediction sets
AN Angelopoulos, S Bates, T Zrnic, MI Jordan
arXiv preprint arXiv:2102.06202, 2021
Semantic uncertainty intervals for disentangled latent spaces
S Sankaranarayanan, AN Angelopoulos, S Bates, Y Romano, P Isola
arXiv preprint arXiv:2207.10074, 2022
Recommendation systems with distribution-free reliability guarantees
AN Angelopoulos, K Krauth, S Bates, Y Wang, MI Jordan
arXiv preprint arXiv:2207.01609, 2022
Conformalized Online Learning: Online Calibration Without a Holdout Set
S Feldman, S Bates, Y Romano
arXiv preprint arXiv:2205.09095, 2022
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Artículos 1–20