Librahttp://mloss.orgUpdates and additions to LibraenThu, 04 Feb 2016 08:51:50 -0000Libra 1.1.2d<html><p>The Libra Toolkit is a collection of algorithms for learning and inference with discrete probabilistic models, including Bayesian networks, Markov networks, dependency networks, sum-product networks, arithmetic circuits, and mixtures of trees. </p> <p>Learning algorithms -- Structure learning for BNs, MNs, DNs, SPNs, and mixtures of trees; learning tractable BNs and MNs with ACs; MN weight learning </p> <p>Inference algorithms -- Mean field, belief propagation, max-product, Gibbs sampling, iterated conditional modes, AC variable elimination, AC exact inference </p> <p>Libra's strengths include structure learning, tractable models, and exploiting sparse factors. </p></html>Daniel Lowd, Amirmohammad RooshenasThu, 04 Feb 2016 08:51:50 -0000 learningapproximate inferencebayesian networksmarkov random fieldsdependency networksarithmetic circuitsexact inferencemarkov networkssum product networks