Knowledge & Reasoning

Towards Time-Aware Knowledge Graph Completion COLING 2016 Tractable Operations for Arithmetic Circuits of Probabilistic Models NeurIPS 2016 BACKSHIFT: Learning causal cyclic graphs from unknown shift interventions NeurIPS 2015 Bandits with Unobserved Confounders: A Causal Approach NeurIPS 2015 Causal Inference by Identification of Vector Autoregressive Processes with Hidden Components ICML 2015 Constraint-based Causal Discovery from Multiple Interventions over Overlapping Variable Sets JMLR 2015 From Dependency to Causality: A Machine Learning Approach JMLR 2015 Incorporating Trustiness and Collective Synonym/Contrastive Evidence into Taxonomy Construction EMNLP 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 Removing systematic errors for exoplanet search via latent causes ICML 2015 Statistical Unfolded Logic Learning ACML 2015 Telling cause from effect in deterministic linear dynamical systems ICML 2015 The Randomized Causation Coefficient JMLR 2015 Towards a Learning Theory of Cause-Effect Inference ICML 2015 An Integer Polynomial Programming Based Framework for Lifted MAP Inference NeurIPS 2014 Causal Discovery with Continuous Additive Noise Models JMLR 2014 Causal Inference through a Witness Protection Program NeurIPS 2014 Causal Strategic Inference in Networked Microfinance Economies NeurIPS 2014 Consistency of Causal Inference under the Additive Noise Model ICML 2014 Correct High-level Robot Behavior in Environments with Unexpected Events RSS 2014 Graphical Models for Recovering Probabilistic and Causal Queries from Missing Data NeurIPS 2014 Learning on graphs using Orthonormal Representation is Statistically Consistent NeurIPS 2014