Projects that are tagged with approximate inference.


Logo JMLR dlib ml 18.17

by davis685 - August 16, 2015, 04:33:39 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 109975 views, 18495 downloads, 4 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.

Changes:

This release adds new clustering tools as well as upgrades the shape_predictor to allow training on datasets with missing landmarks. It also includes bug fixes and minor usability improvements.


Logo JMLR libDAI 0.3.2

by jorism - July 17, 2015, 15:59:55 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 41527 views, 7753 downloads, 4 subscriptions

Rating Whole StarWhole StarWhole StarWhole StarWhole Star
(based on 1 vote)

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.

Changes:

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


Logo JMLR GPML Gaussian Processes for Machine Learning Toolbox 3.6

by hn - July 6, 2015, 12:31:28 CET [ Project Homepage BibTeX Download ] 26983 views, 6284 downloads, 4 subscriptions

Rating Whole StarWhole StarWhole StarWhole StarWhole Star
(based on 2 votes)

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:
  • added a new inference function infGrid_Laplace allowing to use non-Gaussian likelihoods for large grids

  • fixed a bug due to Octave evaluating norm([]) to a tiny nonzero value, modified all lik/lik*.m functions reported by Philipp Richter

  • small bugfixes in covGrid and infGrid

  • bugfix in predictive variance of likNegBinom due to Seth Flaxman

  • bugfix in infFITC_Laplace as suggested by Wu Lin

  • bugfix in covPP{iso,ard}


Logo Libra 1.1.2c

by lowd - June 25, 2015, 00:10:25 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 15021 views, 3277 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.

Changes:

Version 1.1.2c (6/24/2015):

  • Libra can now be installed via OPAM as well. To install OPAM, see: http://opam.ocaml.org/doc/Install.html . Then run: "opam install libra-tk".
  • Updated documentation to describe OPAM installation.

Logo linearizedGP 1.0

by dsteinberg - November 28, 2014, 07:02:54 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 1081 views, 268 downloads, 1 subscription

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

Changes:

Initial Announcement on mloss.org.


Logo libcluster 2.1

by dsteinberg - October 31, 2014, 23:27:57 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 1360 views, 348 downloads, 2 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.

Changes:

Initial Announcement on mloss.org.


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


Logo PILCO policy search framework 0.9

by marc - September 27, 2013, 12:45:12 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 3484 views, 674 downloads, 1 subscription

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

Changes:

Initial Announcement on mloss.org.


Logo GP RTSS 1.0

by marc - March 21, 2012, 08:43:52 CET [ BibTeX BibTeX for corresponding Paper Download ] 2651 views, 828 downloads, 1 subscription

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

Changes:

Initial Announcement on mloss.org.


Logo BRML toolbox 070711

by DavidBarber - July 17, 2011, 19:30:15 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 60567 views, 4107 downloads, 1 subscription

About: Bayesian Reasoning and Machine Learning toolbox

Changes:

Fixed some small bugs and updated some demos.


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

Changes:

Code restructure and bug fix.


Logo JMLR FastInf 1.0

by arielj - June 4, 2010, 14:04:37 CET [ Project Homepage BibTeX Download ] 9066 views, 3132 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.

Changes:

Initial Announcement on mloss.org.


Logo stroll 0.1

by ppletscher - April 1, 2009, 14:32:31 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 4672 views, 1049 downloads, 1 subscription

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

Changes:

Initial Announcement on mloss.org.