causal inference

Mixed Causal Structure Discovery with Application to Prescriptive Pricing IJCAI 2018 Orthogonal Machine Learning: Power and Limitations ICML 2018 Removing Hidden Confounding by Experimental Grounding NeurIPS 2018 Representation Balancing MDPs for Off-policy Policy Evaluation NeurIPS 2018 Representation Learning for Treatment Effect Estimation from Observational Data NeurIPS 2018 Robust Synthetic Control JMLR 2018 Structural Causal Bandits: Where to Intervene? NeurIPS 2018 Tracking State Changes in Procedural Text: a Challenge Dataset and Models for Process Paragraph Comprehension NAACL 2018 Unsupervised Word Influencer Networks from News Streams ACL 2018 Uplift Modeling from Separate Labels NeurIPS 2018 A Causal Framework for Discovering and Removing Direct and Indirect Discrimination IJCAI 2017 A causal framework for explaining the predictions of black-box sequence-to-sequence models EMNLP 2017 A Framework for Optimal Matching for Causal Inference AISTATS 2017 Avoiding Discrimination through Causal Reasoning NeurIPS 2017 Bayesian Inference of Individualized Treatment Effects using Multi-task Gaussian Processes NeurIPS 2017 Causal Effect Inference with Deep Latent-Variable Models NeurIPS 2017 Cause-Effect Knowledge Acquisition and Neural Association Model for Solving A Set of Winograd Schema Problems IJCAI 2017 CHARDA: Causal Hybrid Automata Recovery via Dynamic Analysis IJCAI 2017 Contextual Bandits with Latent Confounders: An NMF Approach AISTATS 2017 Counterfactual Fairness NeurIPS 2017 Deep IV: A Flexible Approach for Counterfactual Prediction ICML 2017 Detecting and Explaining Causes From Text For a Time Series Event EMNLP 2017 Discovering Causal Signals in Images CVPR 2017 Estimating individual treatment effect: generalization bounds and algorithms ICML 2017 Exploiting Causality for Selective Belief Filtering in Dynamic Bayesian Networks (Extended Abstract) IJCAI 2017