causal inference

On the Actionability of Outcome Prediction AAAI 2024 On the Complexity of Identification in Linear Structural Causal Models NeurIPS 2024 On the Impact of Neighbourhood Sampling to Satisfy Sufficiency and Necessity Criteria in Explainable AI CLeaR 2024 On the Misspecification of Linear Assumptions in Synthetic Controls AISTATS 2024 On the Role of Information Structure in Reinforcement Learning for Partially-Observable Sequential Teams and Games NeurIPS 2024 Optimizing Language Models for Human Preferences is a Causal Inference Problem UAI 2024 Out-of-Variable Generalisation for Discriminative Models ICLR 2024 Partial Transportability for Domain Generalization NeurIPS 2024 pgmpy: A Python Toolkit for Bayesian Networks JMLR 2024 PHSIC against Random Consistency and Its Application in Causal Inference IJCAI 2024 Policy Learning for Localized Interventions from Observational Data AISTATS 2024 Position: AI/ML Influencers Have a Place in the Academic Process ICML 2024 Position Debiasing Fine-Tuning for Causal Perception in Long-Term Dialogue IJCAI 2024 Position: Is machine learning good or bad for the natural sciences? ICML 2024 Positivity-free Policy Learning with Observational Data AISTATS 2024 Pragmatic Fairness: Developing Policies with Outcome Disparity Control CLeaR 2024 Prediction-powered Generalization of Causal Inferences ICML 2024 Predictive Coding beyond Correlations ICML 2024 Principles from Clinical Research for NLP Model Generalization NAACL 2024 Probabilities of Causation for Continuous and Vector Variables UAI 2024 Probabilities of Causation with Nonbinary Treatment and Effect AAAI 2024 Products, Abstractions and Inclusions of Causal Spaces UAI 2024 ProMark: Proactive Diffusion Watermarking for Causal Attribution CVPR 2024 Propensity Score Alignment of Unpaired Multimodal Data NeurIPS 2024 Proportion-based Sensitivity Analysis of Uncontrolled Confounding Bias in Causal Inference IJCAI 2024