preprint
Open access
The Libra Toolkit for Probabilistic Models
Research footprint
At a glance
- Citations
- 15
- References
- 9
- Comments
- 0
Paper overview
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.
Record transparency
Publication details
- DOI
- 10.48550/arxiv.1504.00110
- OpenAlex
- W1818632774
- Document type
- preprint
- Language
- EN
- Source
- arXiv (Cornell University)
- Last metadata update
Comments
Log in to join the discussion.