Projects that are tagged with nonparametric bayes.


Logo revrand 1.0.0

by dsteinberg - January 29, 2017, 04:33:54 CET [ Project Homepage BibTeX Download ] 40368 views, 8666 downloads, 0 subscriptions

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About: A library of scalable Bayesian generalised linear models with fancy features

Changes:
  • 1.0 release!
  • Now there is a random search phase before optimization of all hyperparameters in the regression algorithms. This improves the performance of revrand since local optima are more easily avoided with this improved initialisation
  • Regression regularizers (weight variances) associated with each basis object, this approximates GP kernel addition more closely
  • Random state can be set for all random objects
  • Numerous small improvements to make revrand production ready
  • Final report
  • Documentation improvements

Logo JMLR GPstuff 4.7

by avehtari - June 9, 2016, 17:45:15 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 79532 views, 18162 downloads, 0 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:

2016-06-09 Version 4.7

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

New features

  • Simple Bayesian Optimization demo

Improvements

  • Improved use of PSIS
  • More options added to gp_monotonic
  • Monotonicity now works for additive covariance functions with selected variables
  • Possibility to use gpcf_squared.m-covariance function with derivative observations/monotonicity
  • Default behaviour made more robust by changing default jitter from 1e-9 to 1e-6
  • LA-LOO uses the cavity method as the default (see Vehtari et al (2016). Bayesian leave-one-out cross-validation approximations for Gaussian latent variable models. JMLR, accpeted for publication)
  • Selected variables -option works now better with monotonicity

Bugfixes

  • small error in derivative observation computation fixed
  • several minor bug fixes

Logo hca 0.63

by wbuntine - April 26, 2016, 15:35:03 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 58396 views, 7925 downloads, 0 subscriptions

About: Multi-core non-parametric and bursty topic models (HDP-LDA, DCMLDA, and other variants of LDA) implemented in C using efficient Gibbs sampling, with hyperparameter sampling and other flexible controls.

Changes:

Corrected the new normalised Gamma model for topics so it works with multicore. Improvements to documentation. Added an asymptotic version of the generalised Stirling numbers so it longer fails when they run out of bounds on bigger data.


Logo linearizedGP 1.0

by dsteinberg - November 28, 2014, 07:02:54 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 7537 views, 1482 downloads, 0 subscriptions

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

Changes:

Initial Announcement on mloss.org.


Logo Nonparametric Sparse Factor Analysis 1

by davidknowles - July 26, 2013, 01:02:02 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 7182 views, 1642 downloads, 0 subscriptions

About: This is the core MCMC sampler for the nonparametric sparse factor analysis model presented in David A. Knowles and Zoubin Ghahramani (2011). Nonparametric Bayesian Sparse Factor Models with application to Gene Expression modelling. Annals of Applied Statistics

Changes:

Initial Announcement on mloss.org.


Logo The Infinite Hidden Markov Model 0.5

by jvangael - July 21, 2010, 23:41:24 CET [ BibTeX BibTeX for corresponding Paper Download ] 32483 views, 5582 downloads, 0 subscriptions

About: An implementation of the infinite hidden Markov model.

Changes:

Since 0.4: Removed dependency from lightspeed (now using statistics toolbox). Updated to newer matlab versions.


Logo Variational Inference for the Indian Buffet Process 0.1

by finale - May 4, 2009, 16:03:25 CET [ BibTeX BibTeX for corresponding Paper Download ] 15231 views, 2837 downloads, 0 subscriptions

About: Matlab code for performing variational inference in the Indian Buffet Process with a linear-Gaussian likelihood model.

Changes:

Initial Announcement on mloss.org.