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Sequential Deconfounding for Causal Inference with Unobserved Confounders., and . CoRR, (2021)Deconfounding Temporal Autoencoder: Estimating Treatment Effects over Time Using Noisy Proxies., , and . ML4H@NeurIPS, volume 158 of Proceedings of Machine Learning Research, page 143-155. PMLR, (2021)Sequential Deconfounding for Causal Inference with Unobserved Confounders., and . CLeaR, volume 236 of Proceedings of Machine Learning Research, page 934-956. PMLR, (2024)Estimating average causal effects from patient trajectories., , , and . CoRR, (2022)AttDMM: An Attentive Deep Markov Model for Risk Scoring in Intensive Care Units., , , and . KDD, page 3452-3462. ACM, (2021)Combining Observational and Randomized Data for Estimating Heterogeneous Treatment Effects., , , , and . CoRR, (2022)DAPDAG: Domain Adaptation via Perturbed DAG Reconstruction., , , and . CoRR, (2022)Causal Machine Learning for Cost-Effective Allocation of Development Aid., , , and . CoRR, (2024)Estimating Conditional Average Treatment Effects with Missing Treatment Information., , and . CoRR, (2022)Generalizing Off-Policy Learning under Sample Selection Bias., , and . CoRR, (2021)