causal inference

Optimal Transport for Treatment Effect Estimation NeurIPS 2023 Optimal Treatment Allocation for Efficient Policy Evaluation in Sequential Decision Making NeurIPS 2023 Optimized Covariance Design for AB Test on Social Network under Interference NeurIPS 2023 PAC Generalization via Invariant Representations ICML 2023 PADCLIP: Pseudo-labeling with Adaptive Debiasing in CLIP for Unsupervised Domain Adaptation ICCV 2023 Pairwise Causality Guided Transformers for Event Sequences NeurIPS 2023 Pipeline for modeling causal beliefs from natural language ACL 2023 Polynomial-Time Algorithms for Counting and Sampling Markov Equivalent DAGs with Applications JMLR 2023 Preserving Commonsense Knowledge from Pre-trained Language Models via Causal Inference ACL 2023 Pricing Experimental Design: Causal Effect, Expected Revenue and Tail Risk ICML 2023 Probabilities of Causation: Role of Observational Data AISTATS 2023 Probabilities of Potential Outcome Types in Experimental Studies: Identification and Estimation Based on Proxy Covariate Information AAAI 2023 Propensity Matters: Measuring and Enhancing Balancing for Recommendation ICML 2023 Provably Efficient Causal Model-Based Reinforcement Learning for Systematic Generalization AAAI 2023 Proximal Causal Learning of Conditional Average Treatment Effects ICML 2023 PUe: Biased Positive-Unlabeled Learning Enhancement by Causal Inference NeurIPS 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 Rehearsal Learning for Avoiding Undesired Future NeurIPS 2023 Removing Hidden Confounding in Recommendation: A Unified Multi-Task Learning Approach NeurIPS 2023 Returning The Favour: When Regression Benefits From Probabilistic Causal Knowledge ICML 2023 Robust and Agnostic Learning of Conditional Distributional Treatment Effects AISTATS 2023 Robust Causal Graph Representation Learning against Confounding Effects AAAI 2023 Root Cause Identification for Collective Anomalies in Time Series given an Acyclic Summary Causal Graph with Loops AISTATS 2023 Safe Sequential Testing and Effect Estimation in Stratified Count Data AISTATS 2023