mlsanityData to 7 Oct 2026

The Libra Toolkit for Probabilistic Models

arXiv 1504.00110 ↗First posted 1 Apr 2015cs.LG cs.AIcited by 2

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Abstract (arXiv)

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.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). First posted on arXiv 1 Apr 2015.

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2 papers.