Conditional Random Field (CRF) Toolbox for Matlab 1D chains * Java code by Sunita Sarawagi * C++ code by Taku Kudo 2D lattices Written by Kevin Murphy, Mark Schmidt (2006). Last updated: 23 May 2006. This is the code that was used to create the 2D results in this paper Accelerated Training of Conditional Random Fields with Stochastic Meta-Descent S Vishwanathan, N. Schraudolph, M. Schmidt, K. Murphy ICML'06 (Intl Conf on Machine Learning). Note: the published version has some small errors in the experimental results, so the figures will not exactly match the code below. Click here) for a revised version. Now, figures 4 and 6 give can be reproduced using the online code available below. * Download here. Contains C code for BP and mean field inference. * Usage instructions General graphs Written by Kevin Murphy, 2004. This supports 1D chains, 2D lattices and general graphs. This code is no longer supported. The 2D lattice code (above) is better engineered and can be extended to handle general graphs quite easily. * Download here. Contains matlab code for belief propagation. * Usage instructions Other resources for CRFs * Introduction to CRFs, Sutton and McCallum, 2006 to appear. * Conditional Random Fields Webpage by Hanna Wallach, good resource with links to papers and other software.