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Variational Bayesian methods

Variational Bayesian methods are a family of techniques for approximating intractable integrals arising in Bayesian inference and machine learning. They are typically used in complex statistical models consisting of observed variables (usually termed "data") as well as unknown parameters and latent variables, with various sorts of relationships among the…

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Mathematical derivation

Mean field approximation

A duality formula for variational inference

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A more complex example

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Variational Bayesian methods

Nodes95
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Triples10
Avg. degree1.98
Density0.021053
Components1

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Variational Bayesian methods

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see also · 8
Variational Bayesian methods → Bayesian, Calculus, Expectation, Generalized, Maximum, This, Variational, Variational Bayesian

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Important terminology

displaystyle parameters variables variational distribution mathbf distributions posterior probability bayesian values latent bayes em gaussian inference data approximation model expectation

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SubjectPredicateObjectConfidenceSrc
Gibbs samplinginstance ofMarkov chain Monte Carlo methods0.80text
the varianceinstance ofand sometimes higher moments0.80text
Variational Bayesian methodssee alsoVariational0.60section
Variational Bayesian methodssee alsoBayesian0.60section
Variational Bayesian methodssee alsoVariational Bayesian0.60section
Variational Bayesian methodssee alsoExpectation0.60section
Variational Bayesian methodssee alsoGeneralized0.60section
Variational Bayesian methodssee alsoCalculus0.60section
Variational Bayesian methodssee alsoMaximum0.60section
Variational Bayesian methodssee alsoThis0.60section

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