All entries.
Showing Items 131-140 of 535 on page 14 of 54: First Previous 9 10 11 12 13 14 15 16 17 18 19 Next Last

Logo Gibbs RTSS 1.0

by marc - April 4, 2011, 19:58:43 CET [ BibTeX BibTeX for corresponding Paper Download ] 2414 views, 623 downloads, 1 subscription

About: The software provides an implementation of a filter/smoother based on Gibbs sampling, which can be used for inference in dynamical systems.

Changes:

Initial Announcement on mloss.org.


Logo GibbsLDA 0.2

by pxhieu - May 9, 2008, 22:18:52 CET [ Project Homepage BibTeX Download ] 5468 views, 2429 downloads, 1 subscription

About: GibbsLDA++: A C/C++ Implementation of Latent Dirichlet Allocation (LDA) using Gibbs Sampling for parameter estimation and inference. GibbsLDA++ is fast and is designed to analyze hidden/latent topic [...]

Changes:

Initial Announcement on mloss.org.


Logo Gird Soccer Simulator 1.0

by sina_iravanian - April 27, 2011, 16:47:38 CET [ Project Homepage BibTeX Download ] 2539 views, 722 downloads, 1 subscription

About: Grid-Soccer Simulator is a multi-agent soccer simulator in a grid-world environment. The environment provides a test-bed for machine-learning, and control algorithms, especially multi-agent reinforcement learning.

Changes:

Initial Announcement on mloss.org.


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 GMRFLib a library for fast and exact simulation of Gaussian MRF 3

by alipour - September 29, 2008, 03:09:07 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 4967 views, 974 downloads, 2 subscriptions

About: GMRFLib is a library in C for fast and exact simulation of Gaussian Markov Random Fields (GMRF) on graphs.unconditional simulation of a GMRF, conditional simulation from a GMRF

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 ] 1581 views, 518 downloads, 1 subscription

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

Changes:

Initial Announcement on mloss.org.


Logo GPDT Gradient Projection Decomposition Technique 1.01

by sezaza - December 21, 2007, 20:10:43 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 8071 views, 1421 downloads, 1 subscription

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

About: This is a C++ software designed to train large-scale SVMs for binary classification. The algorithm is also implemented in parallel (**PGPDT**) for distributed memory, strictly coupled multiprocessor [...]

Changes:

Initial Announcement on mloss.org.


Logo GPgrid toolkit for fast GP analysis on grid input 0.1

by ejg20 - September 16, 2013, 18:01:16 CET [ BibTeX Download ] 627 views, 236 downloads, 1 subscription

About: GPgrid toolkit for fast GP analysis on grid input

Changes:

Initial Announcement on mloss.org.


Logo JMLR GPML Gaussian Processes for Machine Learning Toolbox 3.4

by hn - November 11, 2013, 14:46:52 CET [ Project Homepage BibTeX Download ] 17194 views, 4198 downloads, 3 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:
  • derivatives w.r.t. inducing points xu in infFITC, infFITC_Laplace, infFITC_EP so that one can treat the inducing points either as fixed given quantities or as additional hyperparameters
  • new GLM likelihood likExp for inter-arrival time modeling
  • new GLM likelihood likWeibull for extremal value regression
  • new GLM likelihood likGumbel for extremal value regression
  • new mean function meanPoly depending polynomially on the data
  • infExact can deal safely with the zero noise variance limit
  • support of GP warping through the new likelihood function likGaussWarp

Logo JMLR GPstuff 4.5

by avehtari - July 22, 2014, 14:03:11 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 10553 views, 2886 downloads, 2 subscriptions

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

About: The GPstuff toolbox is a versatile collection of Gaussian process models and computational tools required for inference. The tools include, among others, various inference methods, sparse approximations and model assessment methods.

Changes:

2014-07-22 Version 4.5

New features

  • Input dependent noise and signal variance.

    • Tolvanen, V., Jylänki, P. and Vehtari, A. (2014). Expectation Propagation for Nonstationary Heteroscedastic Gaussian Process Regression. In Proceedings of IEEE International Workshop on Machine Learning for Signal Processing, accepted for publication. Preprint http://arxiv.org/abs/1404.5443
  • Sparse stochastic variational inference model.

    • Hensman, J., Fusi, N. and Lawrence, N. D. (2013). Gaussian processes for big data. arXiv preprint http://arxiv.org/abs/1309.6835.
  • Option 'autoscale' in the gp_rnd.m to get split normal approximated samples from the posterior predictive distribution of the latent variable.

    • Geweke, J. (1989). Bayesian Inference in Econometric Models Using Monte Carlo Integration. Econometrica, 57(6):1317-1339.

    • Villani, M. and Larsson, R. (2006). The Multivariate Split Normal Distribution and Asymmetric Principal Components Analysis. Communications in Statistics - Theory and Methods, 35(6):1123-1140.

Improvements

  • New unit test environment using the Matlab built-in test framework (the old Xunit package is still also supported).
  • Precomputed demo results (including the figures) are now available in the folder tests/realValues.
  • New demos demonstrating new features etc.
    • demo_epinf, demonstrating the input dependent noise and signal variance model
    • demo_svi_regression, demo_svi_classification
    • demo_modelcomparison2, demo_survival_comparison

Several minor bugfixes


Showing Items 131-140 of 535 on page 14 of 54: First Previous 9 10 11 12 13 14 15 16 17 18 19 Next Last