Causal Inference

Identification and Estimation of the Probabilities of Potential Outcome Types Using Covariate Information in Studies with Non-compliance AAAI 2023 Identify Event Causality with Knowledge and Analogy AAAI 2023 Identifying Selection Bias from Observational Data AAAI 2023 Improved Policy Evaluation for Randomized Trials of Algorithmic Resource Allocation ICML 2023 Improvement-Focused Causal Recourse (ICR) AAAI 2023 Information-Theoretic Causal Discovery and Intervention Detection over Multiple Environments AAAI 2023 Instrumental Variable Estimation of Average Partial Causal Effects ICML 2023 iSCAN: Identifying Causal Mechanism Shifts among Nonlinear Additive Noise Models NeurIPS 2023 Jump Interval-Learning for Individualized Decision Making with Continuous Treatments JMLR 2023 Learning Event-Relevant Factors for Video Anomaly Detection AAAI 2023 Learning Instrumental Variable from Data Fusion for Treatment Effect Estimation AAAI 2023 Meek Separators and Their Applications in Targeted Causal Discovery NeurIPS 2023 Mitigating Biases in Hate Speech Detection from A Causal Perspective EMNLP 2023 Nonlinear Causal Discovery with Latent Confounders ICML 2023 Nonparametric Identifiability of Causal Representations from Unknown Interventions NeurIPS 2023 Non-stationary Experimental Design under Linear Trends NeurIPS 2023 On Learning Necessary and Sufficient Causal Graphs NeurIPS 2023 Optimal Treatment Allocation for Efficient Policy Evaluation in Sequential Decision Making NeurIPS 2023 Optimal Treatment Regimes for Proximal Causal Learning NeurIPS 2023 Optimized Covariance Design for AB Test on Social Network under Interference NeurIPS 2023 Pairwise Causality Guided Transformers for Event Sequences NeurIPS 2023 Physics Guided Neural Networks for Time-Aware Fairness: An Application in Crop Yield Prediction AAAI 2023 Probabilities of Potential Outcome Types in Experimental Studies: Identification and Estimation Based on Proxy Covariate Information AAAI 2023 Rank-Based Causal Discovery for Post-Nonlinear Models AISTATS 2023 Recovering the Graph Underlying Networked Dynamical Systems under Partial Observability: A Deep Learning Approach AAAI 2023