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Additional
belief propagation
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Belief propagation
Belief propagation
, also known as
sum-product message passing
, is a message passing
algorithm
for performing
inference
on
graphical models
, such as
Bayesian networks
and
Markov random fields
. It calculates the
marginal distribution
for each unobserved node, conditional on any observed nodes. Belief propagation is commonly used in
artificial intelligence
and
information theory
and has demonstrated empirical success in numerous applications including
low-density parity-check codes
,
turbo codes
,
free energy
approximation, and
satisfiability
.
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