Description:

The Libra Toolkit is a collection of algorithms for learning and inference with discrete probabilistic models, including Bayesian networks, Markov networks, dependency networks, sum-product networks, arithmetic circuits, and mixtures of trees.

Learning algorithms -- Structure learning for BNs, MNs, DNs, SPNs, and mixtures of trees; learning tractable BNs and MNs with ACs; MN weight learning

Inference algorithms -- Mean field, belief propagation, max-product, Gibbs sampling, iterated conditional modes, AC variable elimination, AC exact inference

Libra's strengths include structure learning, tractable models, and exploiting sparse factors.

Changes to previous version:

Version 1.1.2d (12/29/2015):

• Minor fixes to scripts
• Published in JMLR ML-OSS!

BibTeX Entry: Download

Corresponding Paper BibTeX Entry: Download

Supported Operating Systems: Cygwin, Linux, Mac Os X

Data Formats: Ascii

Tags: Structure Learning, Approximate Inference, Bayesian Networks, Markov Random Fields, Dependency Networks, Arithmetic Circuits, Exact Inference, Markov Networks, Sum Product Networks

Archive: download here

Other available revisons

Version	Changelog	Date
1.1.2d	Version 1.1.2d (12/29/2015): Minor fixes to scripts Published in JMLR ML-OSS!	February 4, 2016, 08:51:50
1.1.2c	Version 1.1.2c (6/24/2015): Libra can now be installed via OPAM as well. To install OPAM, see: http://opam.ocaml.org/doc/Install.html . Then run: "opam install libra-tk". Updated documentation to describe OPAM installation.	June 25, 2015, 00:10:25
1.1.2	Version 1.1.2 (6/10/2015): Switched to 2-clause BSD license; added license headers to all source files. Switched to OASIS build system for much cleaner compilation and installation procedures.	June 11, 2015, 08:07:21
1.1.1	Version 1.1.1 (5/21/2015): Many minor fixes to documentation, scripts, and code.	May 22, 2015, 10:16:52
1.1.0	Version 1.1.0 (3/26/2014): Added SPN library Added API documentation for all libraries Introduced libra script as a unified interface to all programs Many minor improvements to the code, interface, and documentation.	March 27, 2015, 06:29:45
1.0.1	Version 1.0.1 (3/30/2014): Several new algorithms -- acmn, learning ACs using MNs; idspn, SPN structure learning; mtlearn, learning mixtures of trees Several new support programs -- spquery, for exact inference in SPNs; spn2ac, for converting SPNs to ACs Renamed aclearnstruct to acbn Replaced aclearnstruct -noac with separate bnlearn program ...and many more small changes and fixes, throughout!	March 30, 2014, 09:42:00
0.4.0	Version 0.4.0 (7/06/2011): * MF inference in DNs (mf -depnet) * Max-product algorithm for BNs and MNs (maxprod) * MPE inference in ACs (acquery -mpe) * Added support for UAI MN file format. * New fstats utility to get basic file statistics for most file types supported by Libra * And more!	July 6, 2011, 09:40:25
0.3.0	Version 0.3.0 (8/01/2010): New data structure and functions for Markov networks with factors that are trees, tables, conjunctive features, or sets of conjunctive features. Added MN support to ACVE, BP, MF, Gibbs, and more. AC, BN, and MN scoring is now handled by a single program, mscore. Added mscore utility to convert between .xmod and .bif formats, or to go from .xmod/.bif to .mn (Markov network format). Added -noac option to aclearnstruct, so that it can be used to learn a Bayesian network that isn't represented as a circuit. Added dependency network learner (dnlearn) Extended tutorial, revised manual, and added more tests.	August 2, 2010, 07:21:28
0.2.0	Version 0.2.0 (6/08/2010): BP now supports table CPDs, not just trees Gibbs sampling now supports dependency networks with -depnet flag (experimental). Added -norb flag to disable Rao-Blackwellization in Gibbs sampling Fixed expat compilation under OS X Greatly expanded user manual Tweaks to the output of inference algorithms Added more automated tests, based on the tutorial	June 9, 2010, 00:43:28
0.1.0	Initial Announcement on mloss.org.	April 24, 2010, 11:38:24

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