| Debiased machine learning of global and local parameters using regularized Riesz representers V Chernozhukov, WK Newey, R Singh The Econometrics Journal 25 (3), 576--601, 2022 | 316* | 2022 |
| Kernel instrumental variable regression R Singh, M Sahani, A Gretton Advances in Neural Information Processing Systems, 4593-4605, 2019 | 220 | 2019 |
| Automatic Debiased Machine Learning of Causal and Structural Effects V Chernozhukov, WK Newey, R Singh Econometrica 90 (3), 967-1027, 2022 | 184* | 2022 |
| Adversarial Estimation of Riesz Representers V Chernozhukov, W Newey, R Singh, V Syrgkanis arXiv preprint arXiv:2101.00009, 2020 | 57 | 2020 |
| Kernel methods for causal functions: dose, heterogeneous, and incremental response curves R Singh, L Xu, A Gretton Biometrika 111 (2), 497–516, 2024 | 54* | 2024 |
| Kernel Methods for Unobserved Confounding: Negative Controls, Proxies, and Instruments R Singh arXiv preprint arXiv:2012.10315, 2020 | 44 | 2020 |
| A simple and general debiased machine learning theorem with finite-sample guarantees V Chernozhukov, WK Newey, R Singh Biometrika 110 (1), 257-264, 2023 | 37 | 2023 |
| Double robustness for complier parameters and a semi-parametric test for complier characteristics R Singh, L Sun The Econometrics Journal 27 (1), 1-20, 2024 | 34* | 2024 |
| Causal Inference with Corrupted Data: Measurement Error, Missing Values, Discretization, and Differential Privacy A Agarwal, R Singh arXiv preprint arXiv:2107.02780, 2021 | 24 | 2021 |
| Uveal melanoma in BAP1 tumor predisposition syndrome: estimation of risk N Singh, R Singh, RC Bowen, MH Abdel-Rahman, AD Singh American journal of ophthalmology 224, 172-177, 2021 | 24 | 2021 |
| Automatic Debiased Machine Learning for Dynamic Treatment Effects and General Nested Functionals V Chernozhukov, W Newey, R Singh, V Syrgkanis arXiv preprint arXiv:2203.13887, 2022 | 18* | 2022 |
| Sequential Kernel Embedding for Mediated and Time-Varying Dose Response Curves R Singh, L Xu, A Gretton arXiv preprint arXiv:2111.03950, 2021 | 17* | 2021 |
| Debiased kernel methods R Singh arXiv e-prints, arXiv: 2102.11076, 2021 | 12 | 2021 |
| Nested Nonparametric Instrumental Variable Regression: Long Term, Mediated, and Time Varying Treatment Effects I Meza, R Singh arXiv preprint arXiv:2112.14249, 2021 | 11* | 2021 |
| Kernel Ridge Regression Inference R Singh, S Vijaykumar arXiv preprint arXiv:2302.06578, 2023 | 8 | 2023 |
| Automatic Debiased Machine Learning for Covariate Shifts V Chernozhukov, M Newey, WK Newey, R Singh, V Syrgkanis arXiv preprint arXiv:2307.04527, 2023 | 7 | 2023 |
| Generalized Kernel Ridge Regression for Long Term Causal Inference: Treatment Effects, Dose Responses, and Counterfactual Distributions R Singh arXiv preprint arXiv:2201.05139, 2022 | 3 | 2022 |
| Generalized Kernel Ridge Regression for Causal Inference with Missing-at-Random Sample Selection R Singh arXiv preprint arXiv:2111.05277, 2021 | 3 | 2021 |
| Program Evaluation with Remotely Sensed Outcomes A Rambachan, R Singh, D Viviano arXiv preprint arXiv:2411.10959, 2024 | 1 | 2024 |
| Causal Inference Tutorial R Singh MIT Technical Report, 2019 | 1 | 2019 |
Whitney NeweyProfessor of Economics, MITایمیل تأیید شده در mit.edu