observational data

Causal Influences over Social Learning Networks JMLR 2026 IV Co-Scientist: Multi-Agent LLM Framework for Causal Instrumental Variable Discovery CLeaR 2026 Learning control variables and instruments for causal analysis in observational data CLeaR 2026 Comparing Targeting Strategies for Maximizing Social Welfare with Limited Resources ICLR 2025 Complete Characterization for Adjustment in Summary Causal Graphs of Time Series UAI 2025 Compositional Models for Estimating Causal Effects CLeaR 2025 Conditional Average Treatment Effect Estimation Under Hidden Confounders UAI 2025 Deep Neural Cellular Potts Models ICML 2025 Distinguishing Cause from Effect with Causal Velocity Models ICML 2025 Doubly robust identification of treatment effects from multiple environments ICLR 2025 Enumerating Optimal Cost-Constrained Adjustment Sets UAI 2025 Hierarchical Bias-Driven Stratification for Interpretable Causal Effect Estimation AISTATS 2025 Identifying Causal Direction via Variational Bayesian Compression ICML 2025 Local Identifying Causal Relations in the Presence of Latent Variables ICML 2025 Long-Term Individual Causal Effect Estimation via Identifiable Latent Representation Learning IJCAI 2025 Lower Bounds on the Size of Markov Equivalence Classes UAI 2025 Mediation Analysis for Probabilities of Causation AAAI 2025 The Probability of Tiered Benefit: Partial Identification with Robust and Stable Inference CLeaR 2025 Variational Counterfactual Intervention Planning to Achieve Target Outcomes ICML 2025 Alternative Measures of Direct and Indirect Effects PGM 2024 Causal Inference out of Control: Estimating Performativity without Treatment Randomization ICML 2024 Causal-learn: Causal Discovery in Python JMLR 2024 Causal Matching using Random Hyperplane Tessellations CLeaR 2024 Causal Strategic Learning with Competitive Selection AAAI 2024 Data-driven Automated Negative Control Estimation (DANCE): Search for, Validation of, and Causal Inference with Negative Controls JMLR 2024