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Semiparametric Inference For Causal Effects In Graphical Models With Hidden Variables., , and . J. Mach. Learn. Res., (2022)A Semiparametric Approach to Interpretable Machine Learning., , , and . CoRR, (2020)Causal Inference in the Presence of Interference in Sponsored Search Advertising., , , , and . CoRR, (2020)Optimal Training of Fair Predictive Models., , and . CLeaR, volume 177 of Proceedings of Machine Learning Research, page 594-617. PMLR, (2022)Learning Task-Aware Effective Brain Connectivity for fMRI Analysis with Graph Neural Networks (Extended Abstract)., , , , , , , , , and 2 other author(s). IEEE Big Data, page 4995-4996. IEEE, (2022)On Testability and Goodness of Fit Tests in Missing Data Models., and . UAI, volume 216 of Proceedings of Machine Learning Research, page 1467-1477. PMLR, (2023)Estimation of Personalized Effects Associated With Causal Pathways., , and . UAI, page 673-682. AUAI Press, (2018)Semiparametric causal sufficient dimension reduction of multidimensional treatments., , and . UAI, volume 180 of Proceedings of Machine Learning Research, page 1445-1455. PMLR, (2022)On testability of the front-door model via Verma constraints., and . UAI, volume 180 of Proceedings of Machine Learning Research, page 202-212. PMLR, (2022)Deep Dag Learning of Effective Brain Connectivity for FMRI Analysis., , , , , , , , , and 2 other author(s). ISBI, page 1-5. IEEE, (2023)