About:
libDAI provides FOSS implementations of various (approximate) inference methods for graphical models with discrete variables, including Bayesian networks and Markov Random Fields.
Changes:
New features include:
* approximate inference method "Fractional Belief Propagation" (contributed by Frederik Eaton)
* approximate inference method "Tree-Reweighted Belief Propagation"
Apart from that, this release various code cleanups, bug fixes, added examples, and documentation improvements.
- Authors:
Joris Mooij,
Martijn Leisink,
Patrick Pletscher,
Bastian Wemmenhove,
Charles Vaske,
Frederik Eaton,
Giuseppe Passino,
Christian Wojek,
Claudio Lima
- License:
Gpl Version 2 Or Later
- Programming Language:
C++,
Python,
Matlab,
Octave
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- Operating System:
Cygwin,
Linux,
Macosx,
Windows
- Data Formats:
Ascii
- Tags:
Approximate Inference,
Bayesian Networks,
Factor Graphs,
Generalized Belief Propagation,
Graphical Models,
Junction Tree,
Loop Corrections,
Loopy Belief Propagation,
Markov Random Fields,
Mean Field
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