Projects that are tagged with approximate inference.

Logo JMLR GPML Gaussian Processes for Machine Learning Toolbox 4.0

by hn - October 19, 2016, 10:15:05 CET [ Project Homepage BibTeX Download ] 37078 views, 8411 downloads, 4 subscriptions

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About: The GPML toolbox is a flexible and generic Octave/Matlab implementation of inference and prediction with Gaussian process models. The toolbox offers exact inference, approximate inference for non-Gaussian likelihoods (Laplace's Method, Expectation Propagation, Variational Bayes) as well for large datasets (FITC, VFE, KISS-GP). A wide range of covariance, likelihood, mean and hyperprior functions allows to create very complex GP models.


A major code restructuring effort did take place in the current release unifying certain inference functions and allowing more flexibility in covariance function composition. We also redesigned the whole derivative computation pipeline to strongly improve the overall runtime. We finally include grid-based covariance approximations natively.

More generic sparse approximation using Power EP

  • unified treatment of FITC approximation, variational approaches VFE and hybrids

  • inducing input optimisation for all (compositions of) covariance functions dropping the previous limitation to a few standard examples

  • infFITC is now covered by the more generic infGaussLik function

Approximate covariance object unifying sparse approximations, grid-based approximations and exact covariance computations

  • implementation in cov/apx, cov/apxGrid, cov/apxSparse

  • generic infGaussLik unifies infExact, infFITC and infGrid

  • generic infLaplace unifies infLaplace, infFITC_Laplace and infGrid_Laplace

Hiearchical structure of covariance functions

  • clear hierachical compositional implementation

  • no more code duplication as present in covSEiso and covSEard pairs

  • two mother covariance functions

    • covDot for dot-product-based covariances and

    • covMaha for Mahalanobis-distance-based covariances

  • a variety of modifiers: eye, iso, ard, proj, fact, vlen

  • more flexibility as more variants are available and possible

  • all covariance functions offer derivatives w.r.t. inputs

Faster derivative computations for mean and cov functions

  • switched from partial derivatives to directional derivatives

  • simpler and more concise interface of mean and cov functions

  • much faster marginal likelihood derivative computations

  • simpler and more compact code

New mean functions

  • new mean/meanWSPC (Weighted Sum of Projected Cosines or Random Kitchen Sink features) following a suggestion by William Herlands

  • new mean/meanWarp for constructing a new mean from an existing one by means of a warping function adapted from William Herlands

New optimizer

  • added a new minimize_minfunc, contributed by Truong X. Nghiem

New GLM link function

  • added the twice logistic link function util/glm_invlink_logistic2

Smaller fixes

  • two-fold speedup of util/elsympol used by covADD by Truong X. Nghiem

  • bugfix in util/logphi as reported by John Darby

Logo AMIDST Toolbox 0.6.0

by ana - October 14, 2016, 19:35:27 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 4284 views, 653 downloads, 4 subscriptions

About: A Java Toolbox for Scalable Probabilistic Machine Learning.

  • Added sparklink module implementing the integration with Apache Spark. More information here.
  • Fluent pattern in latent-variable-models
  • Predefined model implementing the concept drift detection

Detailed information can be found in the toolbox's web page

Logo JMLR dlib ml 19.2

by davis685 - October 11, 2016, 01:54:09 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 157423 views, 25326 downloads, 5 subscriptions

About: This project is a C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems.


This release adds a number of new features, most important of which is a deep convolutional neural network version of the max-margin object detection algorithm. This tool makes it very easy to create high quality object detectors. See for an introduction.

Logo libcluster 2.3

by dsteinberg - February 27, 2016, 00:36:01 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 4633 views, 1024 downloads, 3 subscriptions

About: An extensible C++ library of Hierarchical Bayesian clustering algorithms, such as Bayesian Gaussian mixture models, variational Dirichlet processes, Gaussian latent Dirichlet allocation and more.


New maximum cluster argument for all algorithms. Also no more matlab interface since it seemed no one was using it, and I cannot support it any longer.

Logo Libra 1.1.2d

by lowd - February 4, 2016, 08:51:50 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 22543 views, 4761 downloads, 3 subscriptions

About: The Libra Toolkit is a collection of algorithms for learning and inference with discrete probabilistic models, including Bayesian networks, Markov networks, dependency networks, sum-product networks, arithmetic circuits, and mixtures of trees.


Version 1.1.2d (12/29/2015):

  • Minor fixes to scripts
  • Published in JMLR ML-OSS!

Logo JMLR libDAI 0.3.2

by jorism - July 17, 2015, 15:59:55 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 51980 views, 9698 downloads, 4 subscriptions

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About: libDAI provides free & open source implementations of various (approximate) inference methods for graphical models with discrete variables, including Bayesian networks and Markov Random Fields.


Release 0.3.2 fixes various bugs and adds GLC (Generalized Loop Corrections) written by Siamak Ravanbakhsh.

Logo linearizedGP 1.0

by dsteinberg - November 28, 2014, 07:02:54 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 2352 views, 516 downloads, 1 subscription

About: Gaussian processes with general nonlinear likelihoods using the unscented transform or Taylor series linearisation.


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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.


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

Logo PILCO policy search framework 0.9

by marc - September 27, 2013, 12:45:12 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 6089 views, 1132 downloads, 1 subscription

About: Data-efficient policy search framework using probabilistic Gaussian process models


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Logo GP RTSS 1.0

by marc - March 21, 2012, 08:43:52 CET [ BibTeX BibTeX for corresponding Paper Download ] 3834 views, 1148 downloads, 1 subscription

About: Gaussian process RTS smoothing (forward-backward smoothing) based on moment matching.


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Logo BRML toolbox 070711

by DavidBarber - July 17, 2011, 19:30:15 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 64047 views, 4673 downloads, 1 subscription

About: Bayesian Reasoning and Machine Learning toolbox


Fixed some small bugs and updated some demos.

About: Matlab implementation of variational gaussian approximate inference for Bayesian Generalized Linear Models.


Code restructure and bug fix.

Logo JMLR FastInf 1.0

by arielj - June 4, 2010, 14:04:37 CET [ Project Homepage BibTeX Download ] 10738 views, 3693 downloads, 1 subscription

About: The library is focused on implementation of propagation based approximate inference methods. Also implemented are a clique tree based exact inference, Gibbs sampling, and the mean field algorithm.


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Logo stroll 0.1

by ppletscher - April 1, 2009, 14:32:31 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 5789 views, 1293 downloads, 1 subscription

About: stroll (STRuctured Output Learning Library) is a library for Structured Output Learning.


Initial Announcement on