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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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OrganITE: Optimal transplant donor organ offering using an individual treatment effect., , , , and . NeurIPS, (2020)Causal Deep Learning: Encouraging Impact on Real-world Problems Through Causality., , , and . Found. Trends Signal Process., 18 (3): 200-309 (2024)NOFLITE: Learning to Predict Individual Treatment Effect Distributions., , and . Trans. Mach. Learn. Res., (2023)ODE Discovery for Longitudinal Heterogeneous Treatment Effects Inference., , , , and . ICLR, OpenReview.net, (2024)Autoencoders for strategic decision support., , , , and . Decis. Support Syst., (2021)Identifiable Energy-based Representations: An Application to Estimating Heterogeneous Causal Effects., , and . AISTATS, volume 151 of Proceedings of Machine Learning Research, page 4158-4177. PMLR, (2022)GOGGLE: Generative Modelling for Tabular Data by Learning Relational Structure., , , and . ICLR, OpenReview.net, (2023)DECAF: Generating Fair Synthetic Data Using Causally-Aware Generative Networks., , , and . NeurIPS, page 22221-22233. (2021)Learning Representations without Compositional Assumptions., , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 21388-21403. PMLR, (2023)HydaLearn., , , , and . Appl. Intell., 53 (5): 5808-5822 (March 2023)