Projects authored by hannes nickisch.


Logo JMLR GPML Gaussian Processes for Machine Learning Toolbox 3.5

by hn - December 8, 2014, 13:54:38 CET [ Project Homepage BibTeX Download ] 20607 views, 4810 downloads, 3 subscriptions

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About: The GPML toolbox is a flexible and generic Octave 3.2.x and Matlab 7.x implementation of inference and prediction in Gaussian Process (GP) models.

Changes:
  • 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)

Logo GradMC 2.00

by tur - April 14, 2014, 15:48:48 CET [ BibTeX Download ] 1871 views, 614 downloads, 1 subscription

About: GradMC is an algorithm for MR motion artifact removal implemented in Matlab

Changes:

Added support for multi-rigid motion correction.


About: The glm-ie toolbox contains scalable estimation routines for GLMs (generalised linear models) and SLMs (sparse linear models) as well as an implementation of a scalable convex variational Bayesian inference relaxation. We designed the glm-ie package to be simple, generic and easily expansible. Most of the code is written in Matlab including some MEX files. The code is fully compatible to both Matlab 7.x and GNU Octave 3.2.x. Probabilistic classification, sparse linear modelling and logistic regression are covered in a common algorithmical framework allowing for both MAP estimation and approximate Bayesian inference.

Changes:

added factorial mean field inference as a third algorithm complementing expectation propagation and variational Bayes

generalised non-Gaussian potentials so that affine instead of linear functions of the latent variables can be used


About: The gmm toolbox contains code for density estimation using mixtures of Gaussians: Starting from simple kernel density estimation with spherical and diagonal Gaussian kernels over manifold Parzen window until mixtures of penalised full Gaussians with only a few components. The toolbox covers many Gaussian mixture model parametrisations from the recent literature. Most prominently, the package contains code to use the Gaussian Process Latent Variable Model for density estimation. Most of the code is written in Matlab 7.x including some MEX files.

Changes:

Initial Announcement on mloss.org


Logo FWTN 1.0

by hn - March 25, 2010, 16:58:24 CET [ Project Homepage BibTeX Download ] 3997 views, 884 downloads, 1 subscription

About: Orthonormal wavelet transform for D dimensional tensors in L levels. Generic quadrature mirror filters and tensor sizes. Runtime is O(n), plain C, MEX-wrapper and demo provided.

Changes:

Initial Announcement on mloss.org.