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.
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}
}