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Comparing the Mean Field Method and Belief Propagation for Approximate Inference in MRFs
edited_book
Publication date:
2001
Publisher:
The MIT Press
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The Handbook of Systems Thinking
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Book Chapter
Publication date:
2001
DOI:
10.7551/mitpress/1100.003.0019
SO-VID:
fe3f4dd0-3cc0-4165-9c3c-dd6b0311f8db
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Book chapters
Mean-field Theory of Learning
The Attenuated Max-Product Algorithm
Tractable Approximate Belief Propagation
Introduction
Information Geometry of Mean-Field Approximation
TAP for Parity Check Error Correcting Codes
Information Geometry of Alpha-Projection in Mean Field Approximation
Adaptive TAP Equations
Some Examples of Recursive Variational Approximations for Bayesian Inference
Saddle-point Methods for Intractable Graphical Models
Comparing the Mean Field Method and Belief Propagation for Approximate Inference in MRFs
Graphical Models and Variational Methods
The TAP Approach to Intensive and Extensive Connectivity Systems
An Idiosyncratic Journey Beyond Mean Field Theory
Mean Field Theory for Graphical Models
From Naive Mean Field Theory to the TAP Equations
Tutorial on Variational Approximation Methods
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