Projects that are tagged with bayesian inference.


Logo JMLR GPstuff 4.6

by avehtari - July 15, 2015, 15:08:06 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 23524 views, 5603 downloads, 2 subscriptions

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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:

2015-07-09 Version 4.6

Development and release branches available at https://github.com/gpstuff-dev/gpstuff

New features

  • Use Pareto smoothed importance sampling (Vehtari & Gelman, 2015) for

  • importance sampling leave-one-out cross-validation (gpmc_loopred.m)

  • importance sampling integration over hyperparameters (gp_ia.m)

  • importance sampling part of the logistic Gaussian process density estimation (lgpdens.m)

  • references:

    • Aki Vehtari and Andrew Gelman (2015). Pareto smoothed importance sampling. arXiv preprint arXiv:1507.02646.
    • Aki Vehtari, Andrew Gelman and Jonah Gabry (2015). Efficient implementation of leave-one-out cross-validation and WAIC for evaluating fitted Bayesian models.
  • New covariance functions

    • gpcf_additive creates a mixture over products of kernels for each dimension reference: Duvenaud, D. K., Nickisch, H., & Rasmussen, C. E. (2011). Additive Gaussian processes. In Advances in neural information processing systems, pp. 226-234.
    • gpcf_linearLogistic corresponds to logistic mean function
    • gpcf_linearMichelismenten correpsonds Michelis Menten mean function

Improvements - faster EP moment calculation for lik_logit

Several minor bugfixes


Logo BayesPy 0.3.5

by jluttine - June 9, 2015, 13:17:00 CET [ Project Homepage BibTeX Download ] 6986 views, 1744 downloads, 3 subscriptions

About: Variational Bayesian inference tools for Python

Changes:
  • Fix indexing bug in VB optimization (not VB-EM)
  • Fix demos

Logo BLOG 0.9.1

by jxwuyi - April 27, 2015, 06:52:05 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 1039 views, 218 downloads, 3 subscriptions

About: Bayesian Logic (BLOG) is a probabilistic modeling language. It is designed for representing relations and uncertainties among real world objects.

Changes:

Initial Announcement on mloss.org.


Logo linearizedGP 1.0

by dsteinberg - November 28, 2014, 07:02:54 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 1088 views, 269 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 MICP 1.04

by kay_brodersen - March 26, 2013, 12:42:04 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 5926 views, 1227 downloads, 2 subscriptions

About: This toolbox implements models for Bayesian mixed-effects inference on classification performance in hierarchical classification analyses.

Changes:

In addition to the existing MATLAB implementation, the toolbox now also contains an R package of the variational Bayesian algorithm for mixed-effects inference.


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

Changes:

Code restructure and bug fix.