| Understanding Belief Propagation and its Generalizations |
| Citation: |
Yedidia, J.S.; Freeman, W.T.; Weiss, Y., "Understanding Belief Propagation and Its Generalizations", Exploring Artificial Intelligence in the New Millennium, ISBN 1558608117, Chap. 8, pp. 239-236, January 2003 (Science & Technology Books) |
| Date: | November 2001 |
| MERL Contact: | Jonathan Yedidia |
"Inference" problems arise in statistical physics, computer vision, error-correcting coding theory, and AI. We explain the principles behind the belief propagation (BP) algorithm, which is an efficient way to solve inference problems based on passing local messages. We develop a unified approach, with examples, notation, and graphical models borrowed from the relevant disciplines.We explain the close connection between the BP algorithm and a detailed example. |
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