Description:

libDAI provides FOSS implementations of various (approximate) inference methods for graphical models with discrete variables, including Bayesian networks and Markov Random Fields.

BibTeX Entry:

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URL:

Project Homepage

Supported Operating Systems:

Cygwin, Linux, Windows

Tags:

Approximate Inference, Bayesian Networks, Factor Graphs, Generalized Belief Propagation, Graphical Models, Loop Corrections, Loopy Belief Propagation, Markov Random Fields, Mean Field, Nips2008, Junct

Archive:

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Comments

Giuseppe Passino (on September 10, 2008, 13:14:13)

I've been using it for a long time. Nice architecture, pretty good features. Some aspects may need optimisation in the implementation. Total lack of documentation makes the use of the library a bit hard at the beginning.

The library can be used also as a stand-alone program specifying factors as raw files. This can be useful in case basic inference tasks are required. In this case, the presence of some commented examples makes the use of the program easier.

Joris Mooij (on September 30, 2008, 23:06:23)

I am pleased to announce a new version of libDAI. It features several optimizations of implementation details and improved doxygen documentation.

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