Efficient Sampling and Structure Learning of Bayesian Networks
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Publication:5057075
DOI10.1080/10618600.2021.2020127OpenAlexW3002588292MaRDI QIDQ5057075
Jack Kuipers, Polina Suter, Giusi Moffa
Publication date: 15 December 2022
Published in: Journal of Computational and Graphical Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1803.07859
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Cites Work
- Parameter priors for directed acyclic graphical models and the characterization of several probability distributions
- Improving the structure MCMC sampler for Bayesian networks by introducing a new edge reversal move
- Geometry of the faithfulness assumption in causal inference
- Addendum on the scoring of Gaussian directed acyclic graphical models
- The max-min hill-climbing Bayesian network structure learning algorithm
- Estimating high-dimensional intervention effects from observational data
- A characterization of Markov equivalence classes for acyclic digraphs
- Being Bayesian about network structure. A Bayesian approach to structure discovery in Bayesian networks
- Improving Markov chain Monte Carlo model search for data mining
- High-dimensional consistency in score-based and hybrid structure learning
- Bayesian Network Structure Learning with Integer Programming: Polytopes, Facets and Complexity
- Causal diagrams for empirical research
- 10.1162/153244302760200696
- 10.1162/153244303321897717
- Bayesian Graphical Models for Discrete Data
- A BIRTH AND DEATH PROCESS FOR BAYESIAN NETWORK STRUCTURE INFERENCE
- Uniform random generation of large acyclic digraphs
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
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