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Abstract: 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. (Update)
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BibTeX entry: (Update)
@misc{ processing-loopy,
author = "Probabilistic Image Processing",
title = "Loopy Belief Propagation And",
url = "citeseer.ist.psu.edu/754364.html" }
Citations (may not include all citations):1543 Probabilistic Reasoning in Intelligent Systems: Networks of .. (context) - Pearl - 1988
110 Markov Random Field Modeling in Computer Vision (context) - Li - 1995
82 Generalized Belief Propagation - Yedidia, Freeman et al. - 2001
36 Advanced Mean Field Methods - Theory and Practice (context) - Opper, Saad - 2001
35 Correctness of Belief Propagation in Gaussian Graphical Mode.. - Weiss - 2001
16 Statistical Physics of Spin Glasses and Information Processi.. (context) - Nishimori - 2001
12 A theory of cooperative phenomena (context) - Kikuchi - 1951
8 Novel iteration schemes for the cluster variation method - Kappen, Wiegerinck - 2002
6 Cluster Variation Method and Image Restoration Problem (context) - Tanaka, Morita - 1995
4 Cluster variation method for non-uniform Ising and Heisenber.. (context) - Morita - 1991
1 Probabilistic Image Processing by means of Bethe Approximati.. (context) - Tanaka, Inoue et al. - 2003
1 Statistical-mechanical Approach to Image Processing (Topical.. (context) - Tanaka - 2002
1 Theoretical Study of Hyperparameter Estimation by Maximizati.. (context) - Tanaka - 2002
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