causal inference

Meaningful Explanations of Black Box AI Decision Systems AAAI 2019 Measuring and Modeling Language Change NAACL 2019 Near-Optimal Reinforcement Learning in Dynamic Treatment Regimes NeurIPS 2019 Neuropathic Pain Diagnosis Simulator for Causal Discovery Algorithm Evaluation NeurIPS 2019 Object Conditioning for Causal Inference UAI 2019 On Multi-Cause Approaches to Causal Inference with Unobserved Counfounding: Two Cautionary Failure Cases and A Promising Alternative AISTATS 2019 On Open-Universe Causal Reasoning UAI 2019 On the Estimation of Treatment Effect with Text Covariates IJCAI 2019 OpenMarkov, an Open-Source Tool for Probabilistic Graphical Models IJCAI 2019 Orthogonal Random Forest for Causal Inference ICML 2019 Path-Specific Counterfactual Fairness AAAI 2019 PC-Fairness: A Unified Framework for Measuring Causality-based Fairness NeurIPS 2019 Perceiving the arrow of time in autoregressive motion NeurIPS 2019 Performance Evaluation in Machine Learning: The Good, the Bad, the Ugly, and the Way Forward AAAI 2019 Policy Evaluation with Latent Confounders via Optimal Balance NeurIPS 2019 Preventing Failures Due to Dataset Shift: Learning Predictive Models That Transport AISTATS 2019 Robustifying Independent Component Analysis by Adjusting for Group-Wise Stationary Noise JMLR 2019 Sample Efficient Active Learning of Causal Trees NeurIPS 2019 Semi-Generative Modelling: Covariate-Shift Adaptation with Cause and Effect Features AISTATS 2019 Separating Wheat from Chaff: Joining Biomedical Knowledge and Patient Data for Repurposing Medications AAAI 2019 Size of Interventional Markov Equivalence Classes in random DAG models AISTATS 2019 SpikeCaKe: Semi-Analytic Nonparametric Bayesian Inference for Spike-Spike Neuronal Connectivity AISTATS 2019 Stability of Linear Structural Equation Models of Causal Inference UAI 2019 Structural Causal Bandits with Non-Manipulable Variables AAAI 2019 The Case for Evaluating Causal Models Using Interventional Measures and Empirical Data NeurIPS 2019