| A new criterion for confounder selection TJ Vander Weele, I Shpitser Biometrics 67 (4), 1406-1413, 2011 | 475 | 2011 |
| Identity uncertainty and citation matching H Pasula, B Marthi, B Milch, SJ Russell, I Shpitser Advances in neural information processing systems 15, 2002 | 436 | 2002 |
| Fair inference on outcomes R Nabi, I Shpitser Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 435 | 2018 |
| Identifiability of path-specific effects C Avin, I Shpitser, J Pearl | 432 | 2005 |
| Identification of joint interventional distributions in recursive semi-Markovian causal models I Shpitser, J Pearl AAAI, 1219-1226, 2006 | 389 | 2006 |
| On the definition of a confounder TJ VanderWeele, I Shpitser Annals of statistics 41 (1), 196, 2013 | 380 | 2013 |
| Semiparametric theory for causal mediation analysis: efficiency bounds, multiple robustness, and sensitivity analysis EJT Tchetgen, I Shpitser Annals of statistics 40 (3), 1816, 2012 | 360 | 2012 |
| Complete identification methods for the causal hierarchy I Shpitser, J Pearl | 302 | 2008 |
| Identification of conditional interventional distributions I Shpitser, J Pearl arXiv preprint arXiv:1206.6876, 2012 | 271 | 2012 |
| On the validity of covariate adjustment for estimating causal effects I Shpitser, T VanderWeele, JM Robins arXiv preprint arXiv:1203.3515, 2012 | 240 | 2012 |
| Nested Markov properties for acyclic directed mixed graphs TS Richardson, RJ Evans, JM Robins, I Shpitser The Annals of Statistics 51 (1), 334-361, 2023 | 141 | 2023 |
| What counterfactuals can be tested I Shpitser, J Pearl arXiv preprint arXiv:1206.5294, 2012 | 137 | 2012 |
| Counterfactual graphical models for longitudinal mediation analysis with unobserved confounding I Shpitser Cognitive science 37 (6), 1011-1035, 2013 | 125 | 2013 |
| Learning optimal fair policies R Nabi, D Malinsky, I Shpitser International Conference on Machine Learning, 4674-4682, 2019 | 123 | 2019 |
| Auto-g-computation of causal effects on a network EJ Tchetgen Tchetgen, IR Fulcher, I Shpitser Journal of the American Statistical Association 116 (534), 833-844, 2021 | 112 | 2021 |
| A systematic review of robustness in deep learning for computer vision: Mind the gap? N Drenkow, N Sani, I Shpitser, M Unberath arXiv preprint arXiv:2112.00639, 2021 | 110 | 2021 |
| Challenges of using text classifiers for causal inference Z Wood-Doughty, I Shpitser, M Dredze Proceedings of the Conference on Empirical Methods in Natural Language …, 2018 | 90 | 2018 |
| Cardiovascular risk prevention and all-cause mortality in primary care patients with an abdominal aortic aneurysm SS Bahia, A Vidal-Diez, SRK Seshasai, I Shpitser, JR Brownrigg, ... Journal of British Surgery 103 (12), 1626-1633, 2016 | 89 | 2016 |
| Effects of treatment on the treated: Identification and generalization I Shpitser, J Pearl arXiv preprint arXiv:1205.2615, 2012 | 89 | 2012 |
| Differentiable causal discovery under unmeasured confounding R Bhattacharya, T Nagarajan, D Malinsky, I Shpitser International Conference on Artificial Intelligence and Statistics, 2314-2322, 2021 | 77 | 2021 |
