Editing Gaussian process (section)

==External links==
{{wikibooks|Gaussian process}}

===Literature===
* [https://gaussianprocess.org The Gaussian Processes Web Site, including the text of Rasmussen and Williams' Gaussian Processes for Machine Learning]
* {{cite arXiv|eprint=1505.02965 |last1=Ebden |first1=Mark |title=Gaussian Processes: A Quick Introduction |year=2015 |class=math.ST }}
* [http://publications.nr.no/917_Rapport.pdf A Review of Gaussian Random Fields and Correlation Functions]
* [https://web.archive.org/web/20180826005000/https://pdfs.semanticscholar.org/c9f2/1b84149991f4d547b3f0f625f710750ad8d9.pdf Efficient Reinforcement Learning using Gaussian Processes]

===Software===

{{further|Comparison of Gaussian process software}}

* [http://www.gaussianprocess.org/gpml/code/matlab/doc/ GPML: A comprehensive Matlab toolbox for GP regression and classification]
* [http://sourceforge.net/projects/kriging STK: a Small (Matlab/Octave) Toolbox for Kriging and GP modeling]
* [http://www.uqlab.com/ Kriging module in UQLab framework (Matlab)]
* [http://codes.arizona.edu/toolbox/ CODES Toolbox: implementations of Kriging, variational kriging and multi-fidelity models (Matlab)]
* [http://au.mathworks.com/matlabcentral/fileexchange/38880: Matlab/Octave function for stationary Gaussian fields]
* [https://github.com/Yelp/MOE Yelp MOE – A black box optimization engine using Gaussian process learning]
* [http://www.sumo.intec.ugent.be/ooDACE ooDACE] {{Webarchive|url=https://web.archive.org/web/20200809021046/http://sumo.intec.ugent.be/ooDACE |date=2020-08-09 }} – A flexible object-oriented Kriging Matlab toolbox.
* [https://web.archive.org/web/20141009045756/http://becs.aalto.fi/en/research/bayes/gpstuff/ GPstuff – Gaussian process toolbox for Matlab and Octave]
* [https://github.com/SheffieldML/GPy GPy – A Gaussian processes framework in Python]
* [https://github.com/GeoStat-Framework/GSTools GSTools - A geostatistical toolbox, including Gaussian process regression, written in Python]
* [http://www.tmpl.fi/gp/ Interactive Gaussian process regression demo]
* [https://github.com/ChristophJud/GPR Basic Gaussian process library written in C++11]
* [http://scikit-learn.org scikit-learn] – A machine learning library for Python which includes Gaussian process regression and classification
* [https://sambo-optimization.github.io SAMBO Optimization] library for Python supports sequential optimization driven by Gaussian process regressor from [[scikit-learn]].
* [https://github.com/modsim/KriKit] - The Kriging toolKit (KriKit) is developed at the Institute of Bio- and Geosciences 1 (IBG-1) of Forschungszentrum Jülich (FZJ)

===Video tutorials===
* [http://videolectures.net/gpip06_mackay_gpb Gaussian Process Basics by David MacKay]
* [http://videolectures.net/epsrcws08_rasmussen_lgp Learning with Gaussian Processes by Carl Edward Rasmussen]
* [http://videolectures.net/mlss07_rasmussen_bigp Bayesian inference and Gaussian processes by Carl Edward Rasmussen]

{{Stochastic processes}}

{{Authority control}}

{{DEFAULTSORT:Gaussian Process}}
[[Category:Stochastic processes]]
[[Category:Kernel methods for machine learning]]
[[Category:Nonparametric Bayesian statistics]]
[[Category:Normal distribution]]