  This work describes a method of approximating matrix permanents efficiently
using belief propagation. We formulate a probability distribution whose
partition function is exactly the permanent, then use Bethe free energy to
approximate this partition function. After deriving some speedups to standard
belief propagation, the resulting algorithm requires $(n^2)$ time per
iteration. Finally, we demonstrate the advantages of using this approximation.
