Causal Inference

Extracting Rare Dependence Patterns via Adaptive Sample Reweighting ICML 2025 FactReasoner: A Probabilistic Approach to Long-Form Factuality Assessment for Large Language Models EMNLP 2025 Factual Knowledge in Language Models: Robustness and Anomalies under Simple Temporal Context Variations ACL 2025 Fairness on Principal Stratum: A New Perspective on Counterfactual Fairness ICML 2025 FairPFN: A Tabular Foundation Model for Causal Fairness ICML 2025 Faithful Inference Chains Extraction for Fact Verification over Multi-view Heterogeneous Graph with Causal Intervention COLING 2025 Falsification of Unconfoundedness by Testing Independence of Causal Mechanisms ICML 2025 Federated Causally Invariant Feature Learning AAAI 2025 Federated Causal Structure Learning with Non-identical Variable Sets ICML 2025 Flow-based Time-aware Causal Structure Learning for Sequential Recommendation IJCAI 2025 GCAD: Anomaly Detection in Multivariate Time Series from the Perspective of Granger Causality AAAI 2025 GCF: Estimating Unobserved Demand Using Graph Causal Forecasting AAAI 2025 Generalized Criterion for Identifiability of Additive Noise Models Using Majorization AISTATS 2025 Generalized Random Forests Using Fixed-Point Trees ICML 2025 Generalizing Causal Effects from Randomized Controlled Trials to Target Populations across Diverse Environments ICML 2025 Generating Synthetic Relational Tabular Data via Structural Causal Models ACL 2025 Generative Intervention Models for Causal Perturbation Modeling ICML 2025 GeoPro-Net: Learning Interpretable Spatiotemporal Prediction Models Through Statistically-Guided Geo-Prototyping AAAI 2025 Gradient-based Causal Feature Selection IJCAI 2025 Heterogeneous Treatment Effect in Time-to-Event Outcomes: Harnessing Censored Data with Recursively Imputed Trees ICML 2025 Higher-order Logical Knowledge Representation Learning IJCAI 2025 Hybrid Local Causal Discovery IJCAI 2025 Identifiability of Causal Graphs under Non-Additive Conditionally Parametric Causal Models JMLR 2025 Identification of Latent Confounders via Investigating the Tensor Ranks of the Nonlinear Observations ICML 2025 Identifying biological perturbation targets through causal differential networks ICML 2025