| 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 | 4515 | 2018 |
| Generalized random forests S Athey, J Tibshirani, S Wager The Annals of Statistics 47 (2), 1148-1178, 2019 | 2980 | 2019 |
| Synthetic difference-in-differences D Arkhangelsky, S Athey, DA Hirshberg, GW Imbens, S Wager American Economic Review 111 (12), 4088-4118, 2021 | 1955 | 2021 |
| Quasi-oracle estimation of heterogeneous treatment effects X Nie, S Wager Biometrika 108 (2), 299-319, 2021 | 1241 | 2021 |
| Policy learning with observational data S Athey, S Wager Econometrica 89 (1), 133-161, 2021 | 1067* | 2021 |
| Dropout training as adaptive regularization S Wager, S Wang, PS Liang Advances in Neural Information Processing Systems, 351-359, 2013 | 850 | 2013 |
| Estimating treatment effects with causal forests: An application S Athey, S Wager Observational Studies 5, 2019 | 784 | 2019 |
| 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 | 759* | 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 | 671 | 2014 |
| High-dimensional asymptotics of prediction: Ridge regression and classification E Dobriban, S Wager The Annals of Statistics 46 (1), 247-279, 2018 | 446 | 2018 |
| Local linear forests R Friedberg, J Tibshirani, S Athey, S Wager Journal of Computational and Graphical Statistics 30 (2), 503-517, 2020 | 346 | 2020 |
| Offline multi-action policy learning: Generalization and optimization Z Zhou, S Athey, S Wager Operations Research 71 (1), 148-183, 2023 | 260 | 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 | 249 | 2021 |
| Adaptive concentration of regression trees, with application to random forests S Wager, G Walther arXiv preprint arXiv:1503.06388, 2015 | 239 | 2015 |
| 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 | 193 | 2016 |
| grf: Generalized random forests J Tibshirani, S Athey, R Friedberg, V Hadad, D Hirshberg, L Miner, ... | 183 | 2025 |
| Estimating heterogeneous treatment effects with right-censored data via causal survival forests Y Cui, MR Kosorok, E Sverdrup, S Wager, R Zhu Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2023 | 165 | 2023 |
| Ranger: A fast implementation of random forests MN Wright, S Wager, P Probst R package version 0.12 1, 730, 2020 | 162 | 2020 |
| Augmented minimax linear estimation DA Hirshberg, S Wager The Annals of Statistics 49 (6), 3206-3227, 2021 | 158* | 2021 |
| 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 | 157 | 2016 |
Susan AtheyThe Economics of Technology Professor, Stanford University Graduate School of BusinessVerified email at stanford.edu
