Project details for GPML Gaussian Processes for Machine Learning Toolbox

Screenshot JMLR GPML Gaussian Processes for Machine Learning Toolbox 3.5

by hn - December 8, 2014, 13:54:38 CET [ Project Homepage BibTeX Download ]

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Description:

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 and mean functions allowing for flexible modeling. The code is fully compatible to Octave 3.2.x.

Changes to previous version:
  • mechanism for specifying hyperparameter priors (together with Roman Garnett and José Vallet)
  • new inference method inf/infGrid allowing efficient inference for data defined on a Cartesian grid (together with Andrew Wilson)
  • new mean/cov functions for preference learning: meanPref/covPref
  • new mean/cov functions for non-vectorial data: meanDiscrete/covDiscrete
  • new piecewise constant nearest neighbor mean function: meanNN
  • new mean functions being predictions from GPs: meanGP and meanGPexact
  • new covariance function for standard additive noise: covEye
  • new covariance function for factor analysis: covSEfact
  • new covariance function with varying length scale : covSEvlen
  • make covScale more general to scaling with a function instead of a scalar
  • bugfix in covGabor* and covSM (due to Andrew Gordon Wilson)
  • bugfix in lik/likBeta.m (suggested by Dali Wei)
  • bugfix in solve_chol.c (due to Todd Small)
  • bugfix in FITC inference mode (due to Joris Mooij) where the wrong mode for post.L was chosen when using infFITC and post.L being a diagonal matrix
  • bugfix in infVB marginal likelihood for likLogistic with nonzero mean function (reported by James Lloyd)
  • removed the combination likErf/infVB as it yields a bad posterior approximation and lacks theoretical justification
  • Matlab and Octave compilation for L-BFGS-B v2.4 and the more recent L-BFGS-B v3.0 (contributed by José Vallet)
  • smaller bugfixes in gp.m (due to Joris Mooij and Ernst Kloppenburg)
  • bugfix in lik/likBeta.m (due to Dali Wei)
  • updated use of logphi in lik/likErf
  • bugfix in util/solve_chol.c where a typing issue occured on OS X (due to Todd Small)
  • bugfix due to Bjørn Sand Jensen noticing that cov_deriv_sq_dist.m was missing in the distribution
  • bugfix in infFITC_EP for ttau->inf (suggested by Ryan Turner)
BibTeX Entry: Download
Supported Operating Systems: Agnostic, Platform Independent
Data Formats: Matlab, Octave
Tags: Classification, Regression, Approximate Inference, Gaussian Processes
Archive: download here

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