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About this paper
Joris Mooij, Bert Kappen
The authors develop loop-corrected belief propagation to improve single-variable marginal estimates in factor graphs with loops. The method estimates distributions over each variable’s neighbors after removing its factors, then adjusts interaction factors to reconcile overlapping estimates. On the ALARM network, maximum marginal error falls from 2.026 × 10⁻¹ with BP to 3.412 × 10⁻⁵ with LCBP; this accuracy result does not establish runtime or scalability advantages.
Summary by alphaXiv.
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