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2005
IEEE

Approximate Inference in Credal Networks by Variational Mean Field Methods

12 years 3 months ago
Approximate Inference in Credal Networks by Variational Mean Field Methods
Graph-theoretical representations for sets of probability measures (credal networks) generally display high complexity, and approximate inference seems to be a natural solution for large networks. This paper introduces a variational approach to approximate inference in credal networks: we show how to formulate mean field approximations using naive (fully factorized) and structured (tree-like) schemes. We discuss the computational advantages of the variational approach, and present examples that illustrate the mechanics of the proposal. Keywords. Credal networks, variational methods, inferences.
Jaime Shinsuke Ide, Fabio Gagliardi Cozman
Added 25 Jun 2010
Updated 25 Jun 2010
Type Conference
Year 2005
Where ISIPTA
Authors Jaime Shinsuke Ide, Fabio Gagliardi Cozman
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