On designing approximate inference algorithms for multiply sectioned Bayesian networks.

Karen H. Jin Dan Wu Libing Wu

Published in: GrC (2009)

Keyphrases

approximate inference
graphical models
belief propagation
multiply sectioned bayesian networks
computational complexity
variational methods
conditional random fields
message passing
probabilistic inference
exact inference
loopy belief propagation
learning algorithm
density estimation
dynamic bayesian networks