| The relative performance of ensemble methods with deep convolutional neural networks for image classification C Ju, A Bibaut, M van der Laan Journal of applied statistics 45 (15), 2800-2818, 2018 | 406 | 2018 |
| Post-contextual-bandit inference A Bibaut, M Dimakopoulou, N Kallus, A Chambaz, M van Der Laan Advances in neural information processing systems 34, 28548-28559, 2021 | 41 | 2021 |
| Fast rates for empirical risk minimization over cadlag functions with bounded sectional variation norm AF Bibaut, MJ van der Laan arXiv, arXiv: 1907.09244, 2019 | 41 | 2019 |
| More efficient off-policy evaluation through regularized targeted learning A Bibaut, I Malenica, N Vlassis, M Van Der Laan International Conference on Machine Learning, 654-663, 2019 | 39 | 2019 |
| On the design of estimators for bandit off-policy evaluation N Vlassis, A Bibaut, M Dimakopoulou, T Jebara International Conference on Machine Learning, 6468-6476, 2019 | 31 | 2019 |
| Finding hotspots: development of an adaptive spatial sampling approach R Andrade-Pacheco, F Rerolle, J Lemoine, L Hernandez, A Meïté, ... Scientific reports 10 (1), 10939, 2020 | 27 | 2020 |
| Risk minimization from adaptively collected data: Guarantees for supervised and policy learning A Bibaut, N Kallus, M Dimakopoulou, A Chambaz, M van Der Laan Advances in neural information processing systems 34, 19261-19273, 2021 | 16 | 2021 |
| CV-TMLE for nonpathwise differentiable target parameters MJ van der Laan, S Rose, MJ van der Laan, A Bibaut, AR Luedtke Targeted Learning in Data Science: Causal Inference for Complex Longitudinal …, 2018 | 15 | 2018 |
| Uniform consistency of the highly adaptive lasso estimator of infinite dimensional parameters MJ van der Laan, AF Bibaut arXiv preprint arXiv:1709.06256, 2017 | 10 | 2017 |
| One-step ahead sequential Super Learning from short times series of many slightly dependent data, and anticipating the cost of natural disasters G Ecoto, A Bibaut, A Chambaz arXiv preprint arXiv:2107.13291, 2021 | 9 | 2021 |
| Near-optimal non-parametric sequential tests and confidence sequences with possibly dependent observations A Bibaut, N Kallus, M Lindon arXiv preprint arXiv:2212.14411, 2022 | 8 | 2022 |
| Rate-adaptive model selection over a collection of black-box contextual bandit algorithms AF Bibaut, A Chambaz, MJ van der Laan arXiv preprint arXiv:2006.03632, 2020 | 8 | 2020 |
| Data-adaptive smoothing for optimal-rate estimation of possibly non-regular parameters AF Bibaut, MJ van der Laan arXiv preprint arXiv:1706.07408, 2017 | 8 | 2017 |
| Sequential causal inference in a single world of connected units A Bibaut, M Petersen, N Vlassis, M Dimakopoulou, M van der Laan arXiv preprint arXiv:2101.07380, 2021 | 7 | 2021 |
| Adaptive sequential design for a single time-series I Malenica, A Bibaut, MJ van der Laan arXiv preprint arXiv:2102.00102, 2021 | 5 | 2021 |
| Inferring the Long-Term Causal Effects of Long-Term Treatments from Short-Term Experiments A Tran, A Bibaut, N Kallus arXiv preprint arXiv:2311.08527, 2023 | 2 | 2023 |
| Sufficient and insufficient conditions for the stochastic convergence of Ces\{a} ro means AF Bibaut, A Luedtke, MJ van der Laan arXiv preprint arXiv:2009.05974, 2020 | 2 | 2020 |
| Generalized Policy Elimination: an efficient algorithm for Nonparametric Contextual Bandits AF Bibaut, A Chambaz, MJ van der Laan Uncertainty in Artificial Intelligence 124, 1099-1108, 2020 | 2 | 2020 |
| Learning the Covariance of Treatment Effects Across Many Weak Experiments A Bibaut, W Chou, S Ejdemyr, N Kallus arXiv preprint arXiv:2402.17637, 2024 | 1 | 2024 |
| Long-Term Causal Inference with Imperfect Surrogates using Many Weak Experiments, Proxies, and Cross-Fold Moments A Bibaut, N Kallus, S Ejdemyr, M Zhao arXiv preprint arXiv:2311.04657, 2023 | 1 | 2023 |
Mark van der LaanJiann-Ping Hsu/Karl E. Peace Professor of Biostatistics & Statistics, University of California Berkeley在 berkeley.edu 的电子邮件经过验证
