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To Impute or not to Impute? Missing Data in Treatment Effect Estimation.

, , , , and . AISTATS, volume 206 of Proceedings of Machine Learning Research, page 3568-3590. PMLR, (2023)

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DECAF: Generating Fair Synthetic Data Using Causally-Aware Generative Networks., , , and . NeurIPS, page 22221-22233. (2021)Triage of 2D Mammographic Images Using Multi-view Multi-task Convolutional Neural Networks., , and . ACM Trans. Comput. Heal., 2 (3): 26:1-26:24 (2021)MIRACLE: Causally-Aware Imputation via Learning Missing Data Mechanisms., , , and . NeurIPS, page 23806-23817. (2021)Multi-view Multi-task Learning for Improving Autonomous Mammogram Diagnosis., , and . MLHC, volume 106 of Proceedings of Machine Learning Research, page 571-591. PMLR, (2019)CASTLE: Regularization via Auxiliary Causal Graph Discovery., , and . NeurIPS, (2020)Towards Causally-Aware Machine Learning.. University of California, Los Angeles, USA, (2021)MAMMO: A Deep Learning Solution for Facilitating Radiologist-Machine Collaboration in Breast Cancer Diagnosis., , and . CoRR, (2018)Formal Analysis of Neural Network-Based Systems in the Aircraft Domain., , , , , , and . FM, volume 13047 of Lecture Notes in Computer Science, page 730-740. Springer, (2021)Siamese Survival Analysis with Competing Risks., , and . ICANN (3), volume 11141 of Lecture Notes in Computer Science, page 260-269. Springer, (2018)To Impute or not to Impute? Missing Data in Treatment Effect Estimation., , , , and . AISTATS, volume 206 of Proceedings of Machine Learning Research, page 3568-3590. PMLR, (2023)