Reasoning

Learning a Distance Metric from a Network NeurIPS 2011 Learning equivalence classes of acyclic models with latent and selection variables from multiple datasets with overlapping variables AISTATS 2011 On Causal Discovery with Cyclic Additive Noise Models NeurIPS 2011 On the Completeness of First-Order Knowledge Compilation for Lifted Probabilistic Inference NeurIPS 2011 Probabilistic Analysis of Correctness of High-Level Robot Behavior with Sensor Error RSS 2011 Solving Decision Problems with Limited Information NeurIPS 2011 The Motion Grammar: Linguistic Perception, Planning, and Control RSS 2011 Block Variable Selection in Multivariate Regression and High-dimensional Causal Inference NeurIPS 2010 Causal discovery in multiple models from different experiments NeurIPS 2010 Efficient Relational Learning with Hidden Variable Detection NeurIPS 2010 Introduction to Causal Inference JMLR 2010 Lifted Inference Seen from the Other Side : The Tractable Features NeurIPS 2010 PLISS: Detecting and Labeling Places Using Online Change-Point Detection RSS 2010 Probabilistic Belief Revision with Structural Constraints NeurIPS 2010 Probabilistic latent variable models for distinguishing between cause and effect NeurIPS 2010 Sparse Instrumental Variables (SPIV) for Genome-Wide Studies NeurIPS 2010 Sufficient covariates and linear propensity analysis AISTATS 2010 Using Descendants as Instrumental Variables for the Identification of Direct Causal Effects in Linear SEMs AISTATS 2010 Bayesian Sparse Factor Models and DAGs Inference and Comparison NeurIPS 2009 Improving the Reliability of Causal Discovery from Small Data Sets Using Argumentation JMLR 2009 Nonlinear directed acyclic structure learning with weakly additive noise models NeurIPS 2009 Non-stationary continuous dynamic Bayesian networks NeurIPS 2009 Properties of Monotonic Effects on Directed Acyclic Graphs JMLR 2009 Time-Varying Dynamic Bayesian Networks NeurIPS 2009 Active Learning of Causal Networks with Intervention Experiments and Optimal Designs JMLR 2008