Causal Inference

Causal Inference under Networked Interference and Intervention Policy Enhancement AISTATS 2021 Causal Inference with Selectively Deconfounded Data AISTATS 2021 Causal Influence Detection for Improving Efficiency in Reinforcement Learning NeurIPS 2021 Causality-aware counterfactual confounding adjustment as an alternative to linear residualization in anticausal prediction tasks based on linear learners ICML 2021 Causal Learning for Socially Responsible AI IJCAI 2021 Causal Modeling with Stochastic Confounders AISTATS 2021 Causal Navigation by Continuous-time Neural Networks NeurIPS 2021 CausalVAE: Disentangled Representation Learning via Neural Structural Causal Models CVPR 2021 CausalWorld: A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning ICLR 2021 CDˆ2CR: Co-reference resolution across documents and domains EACL 2021 Characterizing News Portrayal of Civil Unrest in Hong Kong, 1998–2020 ACL 2021 Collaborative Causal Discovery with Atomic Interventions NeurIPS 2021 Combining Physics and Machine Learning for Network Flow Estimation ICLR 2021 Combining Reinforcement Learning and Causal Models for Robotics Applications IJCAI 2021 Comparing Weak Admissibility Semantics to their Dung-style Counterparts (Extended Abstract) IJCAI 2021 Compositional abstraction error and a category of causal models UAI 2021 Comprehension and Knowledge AAAI 2021 Comprehensive Knowledge Distillation with Causal Intervention NeurIPS 2021 Conditional Distributional Treatment Effect with Kernel Conditional Mean Embeddings and U-Statistic Regression ICML 2021 Conditionally independent data generation UAI 2021 Condition number bounds for causal inference UAI 2021 Confidence in causal discovery with linear causal models UAI 2021 Consistent Nonparametric Methods for Network Assisted Covariate Estimation ICML 2021 Counterfactual Adversarial Learning with Representation Interpolation EMNLP 2021 Counterfactual Explanations in Sequential Decision Making Under Uncertainty NeurIPS 2021