ML Anthology

GPLP: A Local and Parallel Computation Toolbox for Gaussian Process Regression

Chiwoo Park, Jianhua Z. Huang, Yu Ding
MLOSS 2012 pp. 775-779
/mloss/2012/park2012jmlr-gplp/

Abstract

This paper presents the Getting-started style documentation for the local and parallel computation toolbox for Gaussian process regression (GPLP), an open source software package written in Matlab (but also compatible with Octave). The working environment and the usage of the software package will be presented in this paper.

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Cite

Text

Park et al. "GPLP: A Local and Parallel Computation Toolbox for Gaussian Process Regression." Machine Learning Open Source Software, 2012.

Markdown

[Park et al. "GPLP: A Local and Parallel Computation Toolbox for Gaussian Process Regression." Machine Learning Open Source Software, 2012.](https://mlanthology.org/mloss/2012/park2012jmlr-gplp/)

BibTeX

@article{park2012jmlr-gplp,
  title     = {{GPLP: A Local and Parallel Computation Toolbox for Gaussian Process Regression}},
  author    = {Park, Chiwoo and Huang, Jianhua Z. and Ding, Yu},
  journal   = {Machine Learning Open Source Software},
  year      = {2012},
  pages     = {775-779},
  volume    = {13},
  url       = {https://mlanthology.org/mloss/2012/park2012jmlr-gplp/}
}