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Steve Yadlowsky
Steve Yadlowsky
Research Scientist, Google DeepMind
Verified email at google.com - Homepage
Title
Cited by
Cited by
Year
Gemini: a family of highly capable multimodal models
G Team, R Anil, S Borgeaud, JB Alayrac, J Yu, R Soricut, J Schalkwyk, ...
arXiv preprint arXiv:2312.11805, 2023
21922023
Underspecification presents challenges for credibility in modern machine learning
A D'Amour, K Heller, D Moldovan, B Adlam, B Alipanahi, A Beutel, ...
Journal of Machine Learning Research 23 (226), 1-61, 2022
8072022
Clinical implications of revised pooled cohort equations for estimating atherosclerotic cardiovascular disease risk
S Yadlowsky, RA Hayward, JB Sussman, RL McClelland, YI Min, S Basu
Annals of internal medicine 169 (1), 20-29, 2018
2212018
Counterfactual invariance to spurious correlations in text classification
V Veitch, A D'Amour, S Yadlowsky, J Eisenstein
Advances in neural information processing systems 34, 16196-16208, 2021
1632021
Bounds on the conditional and average treatment effect with unobserved confounding factors
S Yadlowsky, H Namkoong, S Basu, J Duchi, L Tian
Annals of statistics 50 (5), 2587, 2022
99*2022
The multiberts: Bert reproductions for robustness analysis
T Sellam, S Yadlowsky, J Wei, N Saphra, A D'Amour, T Linzen, J Bastings, ...
arXiv preprint arXiv:2106.16163, 2021
912021
Deep cox mixtures for survival regression
C Nagpal, S Yadlowsky, N Rostamzadeh, K Heller
Machine Learning for Healthcare Conference, 674-708, 2021
822021
Evaluating treatment prioritization rules via rank-weighted average treatment effects
S Yadlowsky, S Fleming, N Shah, E Brunskill, S Wager
Journal of the American Statistical Association, 1-14, 2024
762024
Off-policy policy evaluation for sequential decisions under unobserved confounding
H Namkoong, R Keramati, S Yadlowsky, E Brunskill
Advances in Neural Information Processing Systems 33, 18819-18831, 2020
762020
Cellpath: Fusion of cellular and traffic sensor data for route flow estimation via convex optimization
C Wu, J Thai, S Yadlowsky, A Pozdnoukhov, A Bayen
Transportation Research Procedia 7, 212-232, 2015
582015
Adaptive sampling probabilities for non-smooth optimization
H Namkoong, A Sinha, S Yadlowsky, JC Duchi
International Conference on Machine Learning, 2574-2583, 2017
462017
Pretraining data mixtures enable narrow model selection capabilities in transformer models
S Yadlowsky, L Doshi, N Tripuraneni
arXiv preprint arXiv:2311.00871, 2023
352023
Estimation and validation of ratio-based conditional average treatment effects using observational data
S Yadlowsky, F Pellegrini, F Lionetto, S Braune, L Tian
Journal of the American Statistical Association 116 (533), 335-352, 2021
262021
Diagnosing model performance under distribution shift
TT Cai, H Namkoong, S Yadlowsky
arXiv preprint arXiv:2303.02011, 2023
252023
Measure what matters: counts of hospitalized patients are a better metric for health system capacity planning for a reopening
S Kashyap, S Gombar, S Yadlowsky, A Callahan, J Fries, BA Pinsky, ...
Journal of the American Medical Informatics Association 27 (7), 1026-1131, 2020
222020
Derivative free optimization via repeated classification
T Hashimoto, S Yadlowsky, J Duchi
International Conference on Artificial Intelligence and Statistics, 2027-2036, 2018
202018
Sloe: A faster method for statistical inference in high-dimensional logistic regression
S Yadlowsky, T Yun, CY McLean, A D'Amour
Advances in neural information processing systems 34, 29517-29528, 2021
142021
Calibration error for heterogeneous treatment effects
Y Xu, S Yadlowsky
International Conference on Artificial Intelligence and Statistics, 9280-9303, 2022
132022
A calibration metric for risk scores with survival data
S Yadlowsky, S Basu, L Tian
Machine Learning for Healthcare Conference, 424-450, 2019
132019
Explaining Practical Differences Between Treatment Effect Estimators with High Dimensional Asymptotics
S Yadlowsky
arXiv preprint arXiv:2203.12538, 2022
9*2022
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