Project details for FastInf

Logo JMLR FastInf 1.0

by arielj - June 4, 2010, 14:04:37 CET [ Project Homepage BibTeX Download ]

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Description:

The FastInf C++ library is designed to perform memory and time efficient approximate inference in large-scale discrete undirected graphical models. The focus of the library is propagation based approximate inference methods, ranging from the basic loopy belief propagation algorithm to propagation based on convex free energies. Various message scheduling schemes that improve on the standard synchronous or asynchronous approaches are included. Also implemented are a clique tree based exact inference, Gibbs sampling, and the mean field algorithm. In addition to inference, FastInf provides parameter estimation capabilities as well as representation and learning of shared parameters. It offers a rich interface that facilitates extension of the basic classes to other inference and learning methods.

Changes to previous version:

Initial Announcement on mloss.org.

BibTeX Entry: Download
URL: Project Homepage
JMLR MLOSS PaperURL: JMLR-MLOSS Paper Homepage
Supported Operating Systems: Macosx, Unix
Data Formats: Binary
Tags: Approximate Inference, Generalized Belief Propagation, Graphical Models, Loopy Belief Propagation, Markov Random Fields, Icml2010
Archive: download here

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