Debiased machine learning of conditional average treatment effects and other causal functions V Semenova, V Chernozhukov Econometrics Journal, 2020 | 261* | 2020 |
Inference on heterogeneous treatment effects in high‐dimensional dynamic panels under weak dependence V Semenova, M Goldman, V Chernozhukov, M Taddy Quantitative Economics 14 (2), 471-510, 2023 | 247* | 2023 |
Regularized Orthogonal Machine Learning for Nonlinear Semiparametric Models D Nekipelov, V Semenova, V Syrgkanis Econometrics Journal, 2021 | 46* | 2021 |
Generalized lee bounds V Semenova arXiv preprint arXiv:2008.12720, 2020 | 34* | 2020 |
Debiased machine learning of set-identified linear models V Semenova Journal of Econometrics 235 (2), 1725-1746, 2023 | 17* | 2023 |
Welfare Analysis in Dynamic Models V Chernozhukov, W Newey, V Semenova arXiv preprint arXiv:1908.09173, 2019 | 15* | 2019 |
Aggregated Intersection Bounds and Aggregated Minimax Values V Semenova arXiv preprint arXiv:2303.00982, 2023 | 8* | 2023 |
Essays in econometrics and machine learning V Semenova Massachusetts Institute of Technology, 2018 | 3 | 2018 |
On the Lower Confidence Band for the Optimal Welfare K Ponomarev, V Semenova arXiv preprint arXiv:2410.07443, 2024 | 1 | 2024 |
Causal Inference with Machine Learning V Chernozhukov, MD Cinelli, E Duflo, I Fernandez-Val, C Hansen, ... | | 2022 |
rmmomin/BootCamp2019 S Condie, R Evans, L Hansen, F Kubler, J Rust, S Scheidegger, ... | | |
ozaltun/BootCamp2019 S Condie, R Evans, L Hansen, F Kubler, J Rust, S Scheidegger, ... | | |
daniel-schaefer/bootcamp2019 Goto Github PK S Condie, R Evans, L Hansen, F Kubler, J Rust, S Scheidegger, ... | | |