causal inference

Causal Effect Identifiability under Partial-Observability ICML 2020 Causal Estimation with Functional Confounders NeurIPS 2020 Causal Feature Learning for Utility-Maximizing Agents PGM 2020 Causal Imitation Learning With Unobserved Confounders NeurIPS 2020 Causal inference in degenerate systems: An impossibility result AISTATS 2020 Causal Inference of Script Knowledge EMNLP 2020 Causal Intervention for Weakly-Supervised Semantic Segmentation NeurIPS 2020 Causally Denoise Word Embeddings Using Half-Sibling Regression AAAI 2020 Causal Modeling for Fairness In Dynamical Systems ICML 2020 Causal Mosaic: Cause-Effect Inference via Nonlinear ICA and Ensemble Method AISTATS 2020 Causal Shapley Values: Exploiting Causal Knowledge to Explain Individual Predictions of Complex Models NeurIPS 2020 Causal Strategic Linear Regression ICML 2020 Causal Transfer for Imitation Learning and Decision Making under Sensor-Shift AAAI 2020 CAUSE: Learning Granger Causality from Event Sequences using Attribution Methods ICML 2020 Characterization of Overlap in Observational Studies AISTATS 2020 Characterizing Distribution Equivalence and Structure Learning for Cyclic and Acyclic Directed Graphs ICML 2020 Characterizing Optimal Mixed Policies: Where to Intervene and What to Observe NeurIPS 2020 Collapsible IDA: Collapsing Parental Sets for Locally Estimating Possible Causal Effects UAI 2020 CookGAN: Causality Based Text-to-Image Synthesis CVPR 2020 Cost-Effective Incentive Allocation via Structured Counterfactual Inference AAAI 2020 COT-GAN: Generating Sequential Data via Causal Optimal Transport NeurIPS 2020 Counterfactual Cross-Validation: Stable Model Selection Procedure for Causal Inference Models ICML 2020 Counterfactual Data Augmentation using Locally Factored Dynamics NeurIPS 2020 Counterfactual Generator: A Weakly-Supervised Method for Named Entity Recognition EMNLP 2020 Counterfactual Prediction for Bundle Treatment NeurIPS 2020