Stefan Wager

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Coauteurs

Susan AtheyThe Economics of Technology Professor, Stanford University Graduate School of BusinessAdresse e-mail validée de stanford.edu
David A. HirshbergEmory UniversityAdresse e-mail validée de emory.edu
guido imbensStanford UniversityAdresse e-mail validée de stanford.edu
Julie TibshiraniSourcegraphAdresse e-mail validée de cs.stanford.edu
Erik SverdrupDepartment of Econometrics & Business Statistics, Monash UniversityAdresse e-mail validée de monash.edu
Xinkun NieStanford UniversityAdresse e-mail validée de stanford.edu
Percy LiangAssociate Professor of Computer Science, Stanford UniversityAdresse e-mail validée de cs.stanford.edu
Sida I. WangFacebook AIAdresse e-mail validée de fb.com
Dmitry ArkhangelskyCEMFIAdresse e-mail validée de cemfi.es
Xu Kuang (许匡)Associate Professor, Stanford Graduate School of BusinessAdresse e-mail validée de stanford.edu
Shuangning LiUniversity of ChicagoAdresse e-mail validée de chicagobooth.edu
Nikolaos IgnatiadisStatistics & Data Science, University of ChicagoAdresse e-mail validée de uchicago.edu
Robert TibshiraniProfessor of Biomedical Data Sciences, and of Statistics, Stanford UniversityAdresse e-mail validée de stanford.edu
Yuchen HuStanford UniversityAdresse e-mail validée de stanford.edu
Vitor HadadApplied Scientist, Amazon Lab126Adresse e-mail validée de amazon.com
Julie JosseSenior Researcher Inria,Adresse e-mail validée de inria.fr
Emma BrunskillAssociate Professor of Computer Science, Stanford UniversityAdresse e-mail validée de cs.stanford.edu
Suzanne de TrevilleProfessor of Operations Management, Faculty of Business and Economics (HEC), University of LausanneAdresse e-mail validée de unil.ch
B EfronProfessor of statistics, Stanford UniversityAdresse e-mail validée de stat.stanford.edu
Trevor HastieProfessor of Statistics, Stanford UniversityAdresse e-mail validée de stanford.edu

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Stefan Wager

Graduate School of Business, Stanford University

Adresse e-mail validée de stanford.edu - Page d'accueil

Statistics Machine Learning Causal Inference


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
Estimation and inference of heterogeneous treatment effects using random forests S Wager, S Athey Journal of the American Statistical Association 113 (523), 1228-1242, 2018	3720	2018
Generalized random forests S Athey, J Tibshirani, S Wager The Annals of Statistics 47 (2), 1148-1178, 2019	2424	2019
Synthetic difference-in-differences D Arkhangelsky, S Athey, DA Hirshberg, GW Imbens, S Wager American Economic Review 111 (12), 4088-4118, 2021	1254	2021
Quasi-oracle estimation of heterogeneous treatment effects X Nie, S Wager Biometrika 108 (2), 299-319, 2021	996	2021
Policy learning with observational data S Athey, S Wager Econometrica 89 (1), 133-161, 2021	893*	2021
Dropout training as adaptive regularization S Wager, S Wang, PS Liang Advances in Neural Information Processing Systems, 351-359, 2013	786	2013
Approximate residual balancing: Debiased inference of average treatment effects in high dimensions S Athey, GW Imbens, S Wager Journal of the Royal Statistical Society Series B 80 (4), 597-623, 2018	696*	2018
Confidence intervals for random forests: The jackknife and the infinitesimal jackknife S Wager, T Hastie, B Efron The journal of machine learning research 15 (1), 1625-1651, 2014	619	2014
Estimating treatment effects with causal forests: An application S Athey, S Wager Observational Studies 5, 2019	614	2019
High-dimensional asymptotics of prediction: Ridge regression and classification E Dobriban, S Wager The Annals of Statistics 46 (1), 247-279, 2018	384	2018
Local linear forests R Friedberg, J Tibshirani, S Athey, S Wager Journal of Computational and Graphical Statistics 30 (2), 503-517, 2020	320	2020
Adaptive concentration of regression trees, with application to random forests S Wager, G Walther arXiv preprint arXiv:1503.06388, 2015	225	2015
Offline multi-action policy learning: Generalization and optimization Z Zhou, S Athey, S Wager Operations Research 71 (1), 148-183, 2023	209	2023
Confidence intervals for policy evaluation in adaptive experiments V Hadad, DA Hirshberg, R Zhan, S Wager, S Athey Proceedings of the national academy of sciences 118 (15), e2014602118, 2021	199	2021
Sequential selection procedures and false discovery rate control MG G'Sell, S Wager, A Chouldechova, R Tibshirani Journal of the Royal Statistical Society: Series B 78 (2), 423-444, 2016	183	2016
High-dimensional regression adjustments in randomized experiments S Wager, W Du, J Taylor, RJ Tibshirani Proceedings of the National Academy of Sciences 113 (45), 12673-12678, 2016	141	2016
grf: Generalized random forests J Tibshirani, S Athey, E Sverdrup, S Wager CRAN: Contributed Packages, 2017	139	2017
Valuing lead time S De Treville, I Bicer, V Chavez-Demoulin, V Hagspiel, N Schürhoff, ... Journal of Operations Management 32 (6), 337-346, 2014	137	2014
Augmented minimax linear estimation DA Hirshberg, S Wager The Annals of Statistics 49 (6), 3206-3227, 2021	136*	2021
Ranger: A fast implementation of random forests MN Wright, S Wager, P Probst R package version 0.12 1, 730, 2020	132	2020

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