Mathematical structures of loopy belief propagation and cluster variation method
نویسنده
چکیده
The mathematical structures of loopy belief propagation are reviewed for graphical models in probabilistic information processing in the stand point of cluster variation method. An extension of adaptive TAP approaches is given by introducing a generalized scheme of the cluster variation method. Moreover the practical message update rules in loopy belief propagation are summarized also for quantum systems. It is suggested that the loopy belief propagation can be reformulated for quantum electron systems by using density matrices of ideal quantum lattice gas system.
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Loopy belief propagation and probabilistic image processing
The hyperparameter estimation in the maximization of the marginal likelihood in the probabilistic image processing is investigated by using the cluster variation method. The algorithms are substantially equivalent to generalized loopy belief propagations.
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