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Benchmarking Heterogeneous Treatment Effect Models through the Lens of Interpretability., , , and . NeurIPS, (2022)SurvITE: Learning Heterogeneous Treatment Effects from Time-to-Event Data., , and . NeurIPS, page 26740-26753. (2021)Defining Expertise: Applications to Treatment Effect Estimation., , , and . CoRR, (2024)Accounting For Informative Sampling When Learning to Forecast Treatment Outcomes Over Time., , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 34855-34874. PMLR, (2023)Estimating Multi-cause Treatment Effects via Single-cause Perturbation., , and . NeurIPS, page 23754-23767. (2021)On Inductive Biases for Heterogeneous Treatment Effect Estimation., and . NeurIPS, page 15883-15894. (2021)A U-turn on Double Descent: Rethinking Parameter Counting in Statistical Learning., , and . CoRR, (2023)Adaptively Identifying Patient Populations With Treatment Benefit in Clinical Trials., , and . CoRR, (2022)A Neural Framework for Generalized Causal Sensitivity Analysis., , , , , and . CoRR, (2023)Doing Great at Estimating CATE? On the Neglected Assumptions in Benchmark Comparisons of Treatment Effect Estimators., and . CoRR, (2021)