ML Anthology

GPstuff: Bayesian Modeling with Gaussian Processes

Jarno Vanhatalo, Jaakko Riihimäki, Jouni Hartikainen, Pasi Jylänki, Ville Tolvanen, Aki Vehtari
MLOSS 2013 pp. 1175-1179
/mloss/2013/vanhatalo2013jmlr-gpstuff/

Abstract

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

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Text

Vanhatalo et al. "GPstuff: Bayesian Modeling with Gaussian Processes." Machine Learning Open Source Software, 2013.

Markdown

[Vanhatalo et al. "GPstuff: Bayesian Modeling with Gaussian Processes." Machine Learning Open Source Software, 2013.](https://mlanthology.org/mloss/2013/vanhatalo2013jmlr-gpstuff/)

BibTeX

@article{vanhatalo2013jmlr-gpstuff,
  title     = {{GPstuff: Bayesian Modeling with Gaussian Processes}},
  author    = {Vanhatalo, Jarno and Riihimäki, Jaakko and Hartikainen, Jouni and Jylänki, Pasi and Tolvanen, Ville and Vehtari, Aki},
  journal   = {Machine Learning Open Source Software},
  year      = {2013},
  pages     = {1175-1179},
  volume    = {14},
  url       = {https://mlanthology.org/mloss/2013/vanhatalo2013jmlr-gpstuff/}
}