mloss.org GPML Gaussian Processes for Machine Learning Toolboxhttp://mloss.orgUpdates and additions to GPML Gaussian Processes for Machine Learning ToolboxenMon, 27 Nov 2017 19:26:13 -0000GPML Gaussian Processes for Machine Learning Toolbox 4.1http://mloss.org/software/view/263/<html><p>The GPML toolbox implements approximate inference algorithms for Gaussian processes such as Expectation Propagation, the Laplace Approximation and Variational Bayes for a wide class of likelihood functions for both regression and classification. It comes with a big algebra of covariance, likelihood, mean and hyperprior functions allowing for flexible modeling. The code is fully compatible to Octave 3.2.x. </p></html>Carl Edward Rasmussen, Hannes NickischMon, 27 Nov 2017 19:26:13 -0000http://mloss.org/software/rss/comments/263http://mloss.org/software/view/263/classificationregressionapproximate inferencegaussian processes