Causal Inference

Change Surfaces for Expressive Multidimensional Changepoints and Counterfactual Prediction JMLR 2019 Characterization and Learning of Causal Graphs with Latent Variables from Soft Interventions NeurIPS 2019 Conditional Independence Testing using Generative Adversarial Networks NeurIPS 2019 Constraint-based Causal Structure Learning with Consistent Separating Sets NeurIPS 2019 Counterfactual Randomization: Rescuing Experimental Studies from Obscured Confounding AAAI 2019 Counterfactual Reasoning in Observational Studies AAAI 2019 Deep Generalized Method of Moments for Instrumental Variable Analysis NeurIPS 2019 Estimating the Causal Effect from Partially Observed Time Series AAAI 2019 GPSfM: Global Projective SFM Using Algebraic Constraints on Multi-View Fundamental Matrices CVPR 2019 Identification of Causal Effects in the Presence of Selection Bias AAAI 2019 Identifying Causal Effects via Context-specific Independence Relations NeurIPS 2019 Identifying Predictive Causal Factors from News Streams EMNLP 2019 Interpretable Almost Matching Exactly With Instrumental Variables UAI 2019 Kernel Instrumental Variable Regression NeurIPS 2019 Learning to Address Health Inequality in the United States with a Bayesian Decision Network AAAI 2019 Likelihood-Free Overcomplete ICA and Applications In Causal Discovery NeurIPS 2019 Machine Learning Estimation of Heterogeneous Treatment Effects with Instruments NeurIPS 2019 Minimum Intervention Cover of a Causal Graph AAAI 2019 Near-Optimal Reinforcement Learning in Dynamic Treatment Regimes NeurIPS 2019 Neuropathic Pain Diagnosis Simulator for Causal Discovery Algorithm Evaluation NeurIPS 2019 Path-Specific Counterfactual Fairness AAAI 2019 PC-Fairness: A Unified Framework for Measuring Causality-based Fairness NeurIPS 2019 Policy Evaluation with Latent Confounders via Optimal Balance NeurIPS 2019 Robust Multi-agent Counterfactual Prediction NeurIPS 2019 Specific and Shared Causal Relation Modeling and Mechanism-Based Clustering NeurIPS 2019