| Removing hidden confounding by experimental grounding N Kallus, AM Puli, U Shalit Advances in neural information processing systems 31, 2018 | 120 | 2018 |
| Out-of-distribution Generalization in the Presence of Nuisance-Induced Spurious Correlations A Puli, LH Zhang, EK Oermann, R Ranganath ICLR 2022, arXiv preprint arXiv:2107.00520, 2021 | 42* | 2021 |
| X-cal: Explicit calibration for survival analysis M Goldstein, X Han, A Puli, A Perotte, R Ranganath Advances in neural information processing systems 33, 18296-18307, 2020 | 30 | 2020 |
| General control functions for causal effect estimation from ivs A Puli, R Ranganath Advances in neural information processing systems 33, 8440-8451, 2020 | 19* | 2020 |
| Nuisances via negativa: Adjusting for spurious correlations via data augmentation A Puli, N Joshi, H He, R Ranganath arXiv preprint arXiv:2210.01302, 2022 | 9 | 2022 |
| Inverse-Weighted Survival Games M Goldstein, X Han, A Puli, T Wies, A Perotte, R Ranganath NeurIPS (cit. on p. 60), 2021 | 9* | 2021 |
| Causal Estimation with Functional Confounders A Puli, AJ Perotte, R Ranganath Advances in neural information processing systems 33, 5115, 2020 | 9 | 2020 |
| When more is less: Incorporating additional datasets can hurt performance by introducing spurious correlations R Compton, L Zhang, A Puli, R Ranganath Machine Learning for Healthcare Conference, 110-127, 2023 | 7 | 2023 |
| Learning invariant representations with missing data M Goldstein, JH Jacobsen, O Chau, A Saporta, AM Puli, R Ranganath, ... Conference on Causal Learning and Reasoning, 290-301, 2022 | 7 | 2022 |
| Don’t blame dataset shift! shortcut learning due to gradients and cross entropy AM Puli, L Zhang, Y Wald, R Ranganath Advances in Neural Information Processing Systems 36, 2023 | 6 | 2023 |
| Individual treatment effect estimation in the presence of unobserved confounding using proxies: a cohort study in stage III non-small cell lung cancer WAC van Amsterdam, JJC Verhoeff, NI Harlianto, GA Bartholomeus, ... Scientific reports 12 (1), 5848, 2022 | 4 | 2022 |
| Contra: Contrarian statistics for controlled variable selection M Sudarshan, A Puli, L Subramanian, S Sankararaman, R Ranganath International conference on artificial intelligence and statistics, 1900-1908, 2021 | 4 | 2021 |
| Beyond Distribution Shift: Spurious Features Through the Lens of Training Dynamics N Murali, A Puli, K Yu, R Ranganath, K Batmanghelich arXiv preprint arXiv:2302.09344, 2023 | 2* | 2023 |
| DIET: Conditional independence testing with marginal dependence measures of residual information M Sudarshan, A Puli, W Tansey, R Ranganath International Conference on Artificial Intelligence and Statistics, 10343-10367, 2023 | 1 | 2023 |
| Bayesian Modeling of Marketing Attribution R Sinha, D Arbour, AM Puli arXiv preprint arXiv:2205.15965, 2022 | 1 | 2022 |
| Development and external validation of a dynamic risk score for early prediction of cardiogenic shock in cardiac intensive care units using machine learning Y Hu, A Lui, M Goldstein, M Sudarshan, A Tinsay, C Tsui, SD Maidman, ... European Heart Journal: Acute Cardiovascular Care, zuae037, 2024 | | 2024 |
| Robust Anomaly Detection for Particle Physics Using Multi-Background Representation Learning A Gandrakota, L Zhang, A Puli, K Cranmer, J Ngadiuba, R Ranganath, ... arXiv preprint arXiv:2401.08777, 2024 | | 2024 |
| A dynamic risk score for early prediction of cardiogenic shock using machine learning Y Hu, A Lui, M Goldstein, M Sudarshan, A Tinsay, C Tsui, S Maidman, ... arXiv preprint arXiv:2303.12888, 2023 | | 2023 |
| Doing Fast Adaptation Fast: Conditionally Independent Deep Ensembles for Distribution Shifts W Yang, AM Puli, AG Wilson, R Ranganath | | 2022 |
| New-Onset Diabetes Assessment Using Artificial Intelligence-Enhanced Electrocardiography N Jethani, A Puli, H Zhang, L Garber, L Jankelson, Y Aphinyanaphongs, ... arXiv preprint arXiv:2205.02900, 2022 | | 2022 |
Rajesh RanganathAssistant Professor, NYUVerified email at cs.princeton.edu
