English

The Libra Toolkit for Probabilistic Models

Machine Learning 2015-04-02 v1 Artificial Intelligence

Abstract

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.

Keywords

Cite

@article{arxiv.1504.00110,
  title  = {The Libra Toolkit for Probabilistic Models},
  author = {Daniel Lowd and Amirmohammad Rooshenas},
  journal= {arXiv preprint arXiv:1504.00110},
  year   = {2015}
}
R2 v1 2026-06-22T09:07:39.446Z