Causal Inference

Learning Bayesian networks with ancestral constraints NeurIPS 2016 Long-term Causal Effects via Behavioral Game Theory NeurIPS 2016 Mutual Information Based Matching for Causal Inference with Observational Data JMLR 2016 Observational-Interventional Priors for Dose-Response Learning NeurIPS 2016 Private Causal Inference AISTATS 2016 Reconstructing Parameters of Spreading Models from Partial Observations NeurIPS 2016 BACKSHIFT: Learning causal cyclic graphs from unknown shift interventions NeurIPS 2015 Bandits with Unobserved Confounders: A Causal Approach NeurIPS 2015 Constraint-based Causal Discovery from Multiple Interventions over Overlapping Variable Sets JMLR 2015 Learnability of Influence in Networks NeurIPS 2015 Learning Causal Graphs with Small Interventions NeurIPS 2015 Local Causal Discovery of Direct Causes and Effects NeurIPS 2015 Rate-Agnostic (Causal) Structure Learning NeurIPS 2015 Feedback Detection for Live Predictors NeurIPS 2014 Graphical Models for Recovering Probabilistic and Causal Queries from Missing Data NeurIPS 2014 On Estimating Causal Effects based on Supplemental Variables AISTATS 2014 Randomized Experimental Design for Causal Graph Discovery NeurIPS 2014 Causal Inference on Time Series using Restricted Structural Equation Models NeurIPS 2013 Data-driven covariate selection for nonparametric estimation of causal effects AISTATS 2013 Graphical Models for Inference with Missing Data NeurIPS 2013 Pairwise Likelihood Ratios for Estimation of Non-Gaussian Structural Equation Models JMLR 2013 Transportability from Multiple Environments with Limited Experiments NeurIPS 2013 Causal discovery with scale-mixture model for spatiotemporal variance dependencies NeurIPS 2012 Controlling Selection Bias in Causal Inference AISTATS 2012 A rational model of causal inference with continuous causes NeurIPS 2011