{"total":19,"rows":[{"id":"2305.16988","title":"Sharp Bounds for Generalized Causal Sensitivity Analysis","created":"2023-05-26","cited_by_count":24,"area":null},{"id":"2209.06203","title":"Normalizing Flows for Interventional Density Estimation","created":"2022-09-13","cited_by_count":21,"area":null},{"id":"2311.16026","title":"A Neural Framework for Generalized Causal Sensitivity Analysis","created":"2023-11-27","cited_by_count":17,"area":null},{"id":"2305.19742","title":"Reliable Off-Policy Learning for Dosage Combinations","created":"2023-05-31","cited_by_count":15,"area":null},{"id":"2306.01424","title":"Partial Counterfactual Identification of Continuous Outcomes with a Curvature Sensitivity Model","created":"2023-06-02","cited_by_count":14,"area":null},{"id":"2211.03374","title":"Deep Causal Learning: Representation, Discovery and Inference","created":"2022-11-07","cited_by_count":11,"area":null},{"id":"2411.03387","title":"Quantifying Aleatoric Uncertainty of the Treatment Effect: A Novel Orthogonal Learner","created":"2024-11-05","cited_by_count":10,"area":null},{"id":"2204.11206","title":"Partial Identification of Dose Responses with Hidden Confounders","created":"2022-04-24","cited_by_count":7,"area":null},{"id":"2306.09520","title":"Ensembled Prediction Intervals for Causal Outcomes Under Hidden Confounding","created":"2023-06-15","cited_by_count":7,"area":null},{"id":"2401.15447","title":"Continuous Treatment Effect Estimation Using Gradient Interpolation and Kernel Smoothing","created":"2024-01-27","cited_by_count":7,"area":null},{"id":"2401.16986","title":"Causal Machine Learning for Cost-Effective Allocation of Development Aid","created":"2024-01-30","cited_by_count":6,"area":null},{"id":"2209.11497","title":"Time Series Causal Link Estimation under Hidden Confounding using Knockoff Interventions","created":"2022-09-23","cited_by_count":5,"area":null},{"id":"2306.14672","title":"PWSHAP: A Path-Wise Explanation Model for Targeted Variables","created":"2023-06-26","cited_by_count":3,"area":null},{"id":"2409.17840","title":"Detecting and Measuring Confounding Using Causal Mechanism Shifts","created":"2024-09-26","cited_by_count":3,"area":null},{"id":"2605.10590","title":"Amortizing Causal Sensitivity Analysis via Prior Data-Fitted Networks","created":"2026-05-11","cited_by_count":3,"area":null},{"id":"2303.10730","title":"Pretrained Vision Models for Predicting High-Risk Breast Cancer Stage","created":"2023-03-19","cited_by_count":1,"area":null},{"id":"2510.13397","title":"Assessing the robustness of heterogeneous treatment effects in survival analysis under informative censoring","created":"2025-10-15","cited_by_count":1,"area":null},{"id":"2205.04296","title":"AODisaggregation: toward global aerosol vertical profiles","created":"2022-05-06","cited_by_count":0,"area":null},{"id":"2301.11921","title":"Using uncertainty-aware machine learning models to study aerosol-cloud interactions","created":"2022-11-30","cited_by_count":0,"area":null}],"next_cursor":null}