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structure learning

341 papers

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SL

Co-occurring keywords

graphical model (863) bayesian network (378) causal discovery (459) directed acyclic graph (242) causal inference (1619) probabilistic modeling (851) probabilistic graphical model (226) gaussian graphical model (106) bayesian inference (1904) markov chain monte carlo (724)

Papers

Proximal Graphical Event Models NIPS 2018
Structure Learning of ${H}$-colorings ALT 2018
Information-theoretic limits of Bayesian network structure learning AISTATS 2017
Information Theoretic Properties of Markov Random Fields, and their Algorithmic Applications NIPS 2017
Permutation-based Causal Inference Algorithms with Interventions NIPS 2017
Bayesian Network Structure Learning with Integer Programming: Polytopes, Facets and Complexity (Extended Abstract) IJCAI 2017
Learning Chordal Markov Networks via Branch and Bound NIPS 2017
Locally Consistent Bayesian Network Scores for Multi-Relational Data IJCAI 2017
Inhomogeneous Hypergraph Clustering with Applications NIPS 2017
Local-to-Global Bayesian Network Structure Learning ICML 2017
Coordinated Multi-Agent Imitation Learning ICML 2017
Learning the Structure of Generative Models without Labeled Data ICML 2017
Learning the Network Structure of Heterogeneous Data via Pairwise Exponential Markov Random Fields AISTATS 2017
Inferring Generative Model Structure with Static Analysis NIPS 2017
Interpretable Structure-Evolving LSTM CVPR 2017
Learning Causal Structures Using Regression Invariance NIPS 2017
Learning Treewidth-Bounded Bayesian Networks with Thousands of Variables NIPS 2016
Active Learning Algorithms for Graphical Model Selection AISTATS 2016
Bayesian Networks: a Combined Tuning Heuristic PGM 2016
On Pruning with the MDL Score PGM 2016
Dynamic Sum Product Networks for Tractable Inference on Sequence Data PGM 2016
An Exact Approach to Learning Probabilistic Relational Model PGM 2016
Enumerating Equivalence Classes of Bayesian Networks using EC Graphs AISTATS 2016
Discriminative Structure Learning of Arithmetic Circuits AISTATS 2016
A Gibbs Sampler for Learning DAGs JMLR 2016