Knowledge & Reasoning

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 Abstraction and Relational learning NeurIPS 2009 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 Nonparametric Latent Feature Models for Link Prediction 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 Bounding Performance Loss in Approximate MDP Homomorphisms NeurIPS 2008 Causal Reasoning with Ancestral Graphs JMLR 2008 Fast Prediction on a Tree NeurIPS 2008 Finding Latent Causes in Causal Networks: an Efficient Approach Based on Markov Blankets NeurIPS 2008 Finding Optimal Bayesian Network Given a Super-Structure JMLR 2008 How memory biases affect information transmission: A rational analysis of serial reproduction NeurIPS 2008 Incremental Identification of Qualitative Models of Biological Systems using Inductive Logic Programming JMLR 2008 Integrating Locally Learned Causal Structures with Overlapping Variables NeurIPS 2008 Interpreting the neural code with Formal Concept Analysis NeurIPS 2008 Learning Control Knowledge for Forward Search Planning JMLR 2008 Nonlinear causal discovery with additive noise models NeurIPS 2008 Online Prediction on Large Diameter Graphs NeurIPS 2008