{"total":51,"rows":[{"id":"2410.08770","title":"Causal machine learning for predicting treatment outcomes","created":"2024-10-11","cited_by_count":74,"area":null},{"id":"2202.07234","title":"Long-term Causal Inference Under Persistent Confounding via Data Combination","created":"2022-02-15","cited_by_count":27,"area":null},{"id":"2406.02873","title":"Prediction-powered Generalization of Causal Inferences","created":"2024-06-05","cited_by_count":15,"area":null},{"id":"2103.06261","title":"A Tree-based Model Averaging Approach for Personalized Treatment Effect Estimation from Heterogeneous Data Sources","created":"2021-03-10","cited_by_count":14,"area":null},{"id":"2103.16689","title":"Multi-Source Causal Inference Using Control Variates","created":"2021-03-30","cited_by_count":13,"area":null},{"id":"2111.08656","title":"Causal Effect Variational Autoencoder with Uniform Treatment","created":"2021-11-16","cited_by_count":8,"area":null},{"id":"2312.03871","title":"Hidden yet quantifiable: A lower bound for confounding strength using randomized trials","created":"2023-12-06","cited_by_count":8,"area":null},{"id":"2406.00317","title":"Combining Experimental and Historical Data for Policy Evaluation","created":"2024-06-01","cited_by_count":6,"area":null},{"id":"2412.11511","title":"Constructing Confidence Intervals for Average Treatment Effects from Multiple Datasets","created":"2024-12-16","cited_by_count":6,"area":null},{"id":"2112.13502","title":"Deep Treatment-Adaptive Network for Causal Inference","created":"2021-12-27","cited_by_count":5,"area":null},{"id":"2301.05491","title":"Efficient and robust transfer learning of optimal individualized treatment regimes with right-censored survival data","created":"2023-01-13","cited_by_count":5,"area":null},{"id":"2503.09494","title":"Representation Retrieval Learning for Heterogeneous Data Integration","created":"2025-03-12","cited_by_count":5,"area":null},{"id":"2506.22754","title":"Doubly robust estimation of causal effects for random object outcomes with continuous treatments","created":"2025-06-28","cited_by_count":5,"area":null},{"id":"2306.01086","title":"Multi-Study R-Learner for Estimating Heterogeneous Treatment Effects Across Studies Using Statistical Machine Learning","created":"2023-06-01","cited_by_count":4,"area":null},{"id":"2402.15137","title":"Benchmarking Observational Studies with Experimental Data under Right-Censoring","created":"2024-02-23","cited_by_count":4,"area":null},{"id":"2402.17042","title":"Towards Generalizing Inferences from Trials to Target Populations","created":"2024-02-26","cited_by_count":4,"area":null},{"id":"2404.15746","title":"Collaborative Heterogeneous Causal Inference Beyond Meta-analysis","created":"2024-04-24","cited_by_count":4,"area":null},{"id":"2406.13966","title":"Causal Inference with Latent Variables: Recent Advances and Future Prospectives","created":"2024-06-20","cited_by_count":4,"area":null},{"id":"2412.08869","title":"Beyond Reweighting: On the Predictive Role of Covariate Shift in Effect Generalization","created":"2024-12-12","cited_by_count":4,"area":null},{"id":"2503.14795","title":"The Hardness of Validating Observational Studies with Experimental Data","created":"2025-03-19","cited_by_count":4,"area":null},{"id":"2510.15217","title":"Reflections from Research Roundtables at the Conference on Health, Inference, and Learning (CHIL) 2025","created":"2025-10-17","cited_by_count":4,"area":null},{"id":"2105.00581","title":"Robust Sample Weighting to Facilitate Individualized Treatment Rule Learning for a Target Population","created":"2021-05-03","cited_by_count":3,"area":null},{"id":"2306.06002","title":"Causal Effect Estimation from Observational and Interventional Data Through Matrix Weighted Linear Estimators","created":"2023-06-09","cited_by_count":3,"area":null},{"id":"2502.06231","title":"Falsification of Unconfoundedness by Testing Independence of Causal Mechanisms","created":"2025-02-10","cited_by_count":3,"area":null},{"id":"2407.09387","title":"Meta-Analysis with Untrusted Data","created":"2024-07-12","cited_by_count":2,"area":null},{"id":"2409.01794","title":"Estimating Joint Interventional Distributions from Marginal Interventional Data","created":"2024-09-03","cited_by_count":2,"area":null},{"id":"2505.15215","title":"Clustering and Pruning in Causal Data Fusion","created":"2025-05-21","cited_by_count":2,"area":null},{"id":"2505.17961","title":"Federated Causal Inference from Multi-Site Observational Data via Propensity Score Aggregation","created":"2025-05-23","cited_by_count":2,"area":null},{"id":"2512.23408","title":"Probabilistic Modelling is Sufficient for Causal Inference","created":"2025-12-29","cited_by_count":2,"area":null},{"id":"2605.01311","title":"The Partial Testimony of Logs: Evaluation of Language Model Generation under Confounded Model Choice","created":"2026-05-02","cited_by_count":2,"area":null},{"id":"2211.00249","title":"Robust Direct Learning for Causal Data Fusion","created":"2022-11-01","cited_by_count":1,"area":null},{"id":"2410.21343","title":"Combining Incomplete Observational and Randomized Data for Heterogeneous Treatment Effects","created":"2024-10-28","cited_by_count":1,"area":null},{"id":"2505.24413","title":"Multi-task Learning for Heterogeneous Multi-source Block-Wise Missing Data","created":"2025-05-30","cited_by_count":1,"area":null},{"id":"2603.03785","title":"Observationally Informed Adaptive Causal Experimental Design","created":"2026-03-04","cited_by_count":1,"area":null},{"id":"2603.19186","title":"Improving RCT-Based Treatment Effect Estimation Under Covariate Mismatch via Calibrated Alignment","created":"2026-03-19","cited_by_count":1,"area":null},{"id":"2206.06699","title":"Generalizing experimental findings: identification beyond adjustments","created":"2022-06-14","cited_by_count":0,"area":null},{"id":"2310.14763","title":"Externally Valid Policy Evaluation Combining Trial and Observational Data","created":"2023-10-23","cited_by_count":0,"area":null},{"id":"2410.15655","title":"Accounting for Missing Covariates in Heterogeneous Treatment Estimation","created":"2024-10-21","cited_by_count":0,"area":null},{"id":"2501.08067","title":"Optimal Policy Adaptation under Covariate Shift","created":"2025-01-14","cited_by_count":0,"area":null},{"id":"2501.08888","title":"A Partial Initialization Strategy to Mitigate the Overfitting Problem in CATE Estimation with Hidden Confounding","created":"2025-01-15","cited_by_count":0,"area":null},{"id":"2506.01191","title":"Uncovering Bias Mechanisms in Observational Studies","created":"2025-06-01","cited_by_count":0,"area":null},{"id":"2506.12304","title":"Conditional Average Treatment Effect Estimation Under Hidden Confounders","created":"2025-06-14","cited_by_count":0,"area":null},{"id":"2509.18148","title":"Augmenting Limited and Biased RCTs through Pseudo-Sample Matching-Based Observational Data Fusion Method","created":"2025-09-16","cited_by_count":0,"area":null},{"id":"2510.25924","title":"Transferring Causal Effects using Proxies","created":"2025-10-29","cited_by_count":0,"area":null},{"id":"2511.19735","title":"Integrating RCTs, RWD, AI/ML and Statistics: Next-Generation Evidence Synthesis","created":"2025-11-24","cited_by_count":0,"area":null},{"id":"2602.19703","title":"Testing Effect Homogeneity and Confounding in High-Dimensional Experimental and Observational Studies","created":"2026-02-23","cited_by_count":0,"area":null},{"id":"2604.00915","title":"Orthogonal Learner for Estimating Heterogeneous Long-Term Treatment Effects","created":"2026-04-01","cited_by_count":0,"area":null},{"id":"2604.03772","title":"Debiased Machine Learning for Conformal Prediction of Counterfactual Outcomes Under Runtime Confounding","created":"2026-04-04","cited_by_count":0,"area":null},{"id":"2605.15483","title":"Improving the Efficiency of Subgroup Analysis in Randomized Controlled Trials with TMLE","created":"2026-05-14","cited_by_count":0,"area":null},{"id":"2606.24160","title":"An Introduction to Causal Reinforcement Learning","created":"2026-06-23","cited_by_count":0,"area":"deeprl"},{"id":"2606.27114","title":"Cross-Head Attention Uplift Network with Inverse Propensity Score under Unobserved Confounding","created":"2026-06-25","cited_by_count":0,"area":null}],"next_cursor":null}