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arxiv: 1504.00110 · v1 · pith:PLOLCDFFnew · submitted 2015-04-01 · 💻 cs.LG · cs.AI

The Libra Toolkit for Probabilistic Models

classification 💻 cs.LG cs.AI
keywords inferencelibramodelsnetworkslearningalgorithmsexactprobabilistic
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The Libra Toolkit is a collection of algorithms for learning and inference with discrete probabilistic models, including Bayesian networks, Markov networks, dependency networks, and sum-product networks. Compared to other toolkits, Libra places a greater emphasis on learning the structure of tractable models in which exact inference is efficient. It also includes a variety of algorithms for learning graphical models in which inference is potentially intractable, and for performing exact and approximate inference. Libra is released under a 2-clause BSD license to encourage broad use in academia and industry.

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