= Junction tree algorithm
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The junction tree algorithm performs exact inference in a finite <probabilistic graphical model>. First moralize a <Bayesian network> if necessary; then apply <triangulation of an undirected graph>, organize its <maximal cliques> into a <junction tree>, and assign each original factor to one containing clique. Inward and outward <junction-tree sum-product messages> compute the <normalizing constant> and <marginal distributions>. Its cost depends exponentially on the largest clique's number of variables, rather than necessarily on the total number of variables.
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