FastInf homepage

version 1.0


The FastInf c++ library was designed to perform memory and time efficient approximate inference in large relational undirected graphical models, and to allow parameter and structure learning of template Markov random fields.

The library was written by Ariel Jaimovich, Ofer Meshi, Ian Mcgraw and Gal Elidan in the labs of Prof Nir Friedman (School of Computer Science and Engineering in the Hebrew University) and of Prof. Daphne Koller  (Computer Science Dept. in Stanford University).

FastInf is distributed under the terms of the GPLv3 license for public software.

Click here for installing the library Download_and_install.htmlDocumentation.htmlshapeimage_1_link_0

© Copyright 2009 Ariel Jaimovich, Ofer Meshi, Ian McGraw and Gal Elidan

Click here for documentation on how to use the library