© 2005 Society for Imprecise Probability: Theories and Applications, SIPTA. All rights reserved. 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.
|Original language||American English|
|State||Published - 1 Jan 2005|
|Event||4th International Symposium on Imprecise Probabilities and Their Applications, ISIPTA 2005 - |
Duration: 1 Jan 2005 → …
|Conference||4th International Symposium on Imprecise Probabilities and Their Applications, ISIPTA 2005|
|Period||1/01/05 → …|