Causal Inference

Causal de Finetti: On the Identification of Invariant Causal Structure in Exchangeable Data NeurIPS 2023 Causal-DFQ: Causality Guided Data-Free Network Quantization ICCV 2023 CausalDialogue: Modeling Utterance-level Causality in Conversations ACL 2023 Causal Discovery for Non-stationary Non-linear Time Series Data Using Just-In-Time Modeling CLeaR 2023 Causal discovery from observational and interventional data across multiple environments NeurIPS 2023 Causal Discovery from Subsampled Time Series with Proxy Variables NeurIPS 2023 Causal Discovery with Latent Confounders Based on Higher-Order Cumulants ICML 2023 Causal Discovery with Score Matching on Additive Models with Arbitrary Noise CLeaR 2023 Causal Discovery with Unobserved Confounding and Non-Gaussian Data JMLR 2023 Causal Document-Grounded Dialogue Pre-training EMNLP 2023 Causal effect estimation from observational and interventional data through matrix weighted linear estimators UAI 2023 Causal Effect Identification in Cluster DAGs AAAI 2023 Causal Effect Identification in Uncertain Causal Networks NeurIPS 2023 Causal Effect Regularization: Automated Detection and Removal of Spurious Correlations NeurIPS 2023 Causal Entropy Optimization AISTATS 2023 Causal Estimation for Text Data with (Apparent) Overlap Violations ICLR 2023 Causal Fairness for Outcome Control NeurIPS 2023 Causal Imitability Under Context-Specific Independence Relations NeurIPS 2023 Causal Imitation Learning via Inverse Reinforcement Learning ICLR 2023 Causal Inference from Text: Unveiling Interactions between Variables EMNLP 2023 Causal Inference under Interference and Model Uncertainty CLeaR 2023 Causal Inference with Conditional Instruments Using Deep Generative Models AAAI 2023 Causal information splitting: Engineering proxy features for robustness to distribution shifts UAI 2023 Causal Interpretation of Self-Attention in Pre-Trained Transformers NeurIPS 2023 Causal Intervention and Counterfactual Reasoning for Multi-modal Fake News Detection ACL 2023