A tutorial on variational Bayesian inference

Artificial Intelligence Review

Volumn 38, Issue 2, 2012, Pages 85-95

  Fox, Charles W ^a   Roberts, Stephen J ^b  

^a UNIVERSITY OF SHEFFIELD   (United Kingdom)

^b UNIVERSITY OF OXFORD   (United Kingdom)

Author keywords

Mean field; Tutorial; Variational Bayes

Indexed keywords

GRAPHICAL MODEL; KL-DIVERGENCE; MEAN-FIELD; STATISTICAL PHYSICS; TUTORIAL; VARIATIONAL BAYES; VARIATIONAL BAYESIAN;

INFERENCE ENGINES;

BAYESIAN NETWORKS;

EID: 84864561384     PISSN: 02692821     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10462-011-9236-8     Document Type: Review

References (4)

1. Attias H (2000) A variational Bayesian framework for graphical models. In: Advances in neural information processing systems. MIT Press
2. Bernardo JM, Smith AFM (2000) Bayesian theory. Wiley, London
3. Bishop CM, Winn JM, Spiegelhalter D (2002) VIBES: A variational inference engine for Bayesian networks. In: Advances in neural information processing systems
4. Winn J, Bishop C (2005) Variational message passing. J Mach Learn Res 6:661-694