Learning Gaussian graphical models with fractional marginal pseudo-likelihood

Janne Leppä-aho; Johan Pensar; Teemu Roos; Jukka Corander

doi:10.1016/j.ijar.2017.01.001

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Learning Gaussian graphical models with fractional marginal pseudo-likelihood

Janne Leppä-aho Johan Pensar Teemu Roos Jukka Corander

Year: 2017 Journal: International Journal of Approximate Reasoning Vol: 83 Pages: 21-42 Publisher: Elsevier BV

DOI: 10.1016/j.ijar.2017.01.001

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Keywords:

Graphical model Marginal likelihood Gaussian Inference Likelihood function Graph Factor graph Estimator Algorithm Computer science Bayesian inference Bayesian network Mathematics Bayesian probability Simple (philosophy) Artificial intelligence Machine learning Theoretical computer science Estimation theory Statistics

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Bayesian Modeling and Causal Inference

Physical Sciences → Computer Science → Artificial Intelligence

Bayesian Methods and Mixture Models

Physical Sciences → Computer Science → Artificial Intelligence

Statistical Methods and Bayesian Inference

Physical Sciences → Mathematics → Statistics and Probability

Learning Gaussian graphical models with fractional marginal pseudo-likelihood

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