… is the introduction of counting BP, a novel, scaleable belief propagation approach. CBP …
given the evidence, and applies a modified belief propagation to this factor graph. It has been …

… learns to estimate accurate model counts from a training set of 10’s of problems and generalize
to problems that are significantly harder for an exact model counter to solve. Compared …

… Count is that instead of relying on solution samples, we use a variant of belief propagation to
… Finally, we will describe our variation of the belief propagation algorithm which is key to the …

… This cluster counting approach can be naturally written in terms of a new factor graph … of
the Belief Propagation inference framework, we can efficiently approximate cluster counts in …

… count (number of solutions) of Boolean formulas, and present two techniques that compute
estimates of these counts… estimation, namely, variations of Belief Propagation (BP). Our …

… Belief propagation must be altered slightly to take these counts into account. Since all the
atoms in a supernode have the same counts, we can set n(X, F) = n(s, F), where s is an …

… exact weighted counting for a constraint it is clear that we achieve domain consistency for it
and after some iterations of belief propagation we should reach standard propagation’s fixed …

… the evidence is double counted, all evidence is equally double counted. For networks with a
… relating the beliefs estimated by loopy belief propagation and the correct beliefs. This allows …

… free energies of basic clusters of nodes, minus the free energy of over-counted cluster
intersections, minus the free energy of the over-counted intersections of intersections, and so on. …

… Belief propagation must be altered slightly to take these counts into account. Since all the
atoms in a supernode have the same counts, we can set n(X, F) = n(s, F), where s is an …