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pyGPs is a library containing an object-oriented python implementation for Gaussian Process (GP) regression and classification.
Python Matlab

Merge pull request #22 from marionmari/initialization

looks good to me. In terms of documentation we should update ProductOfMean to CompositeMean then? How does it work for the sum? Is this still SumOfMean or also Composite?
latest commit 1a624f53f0
@marionmari authored

Marion Neumann [marion dot neumann at uni-bonn dot de]
Daniel Marthaler [dan dot marthaler at gmail dot com]
Shan Huang [schan dot huang at gmail dot com]
Kristian Kersting [kristian dot kersting at cs dot tu-dortmund dot de]

This file is part of pyGPs.
The software package is released under the BSD 2-Clause (FreeBSD) License.

Copyright (c) by
Marion Neumann, Daniel Marthaler, Shan Huang & Kristian Kersting, 18/02/2014

pyGPs is a library containing code for Gaussian Process (GP) Regression and Classification.

Here is the online documentation: ONLINE documentation.

pyGPs is an object-oriented implementation of GPs. Its functionality follows roughly the gpml matlab implementation by Carl Edward Rasmussen and Hannes Nickisch (Copyright (c) by Carl Edward Rasmussen and Hannes Nickisch, 2013-01-21).

Standard GP regression and (binary) classification as well as FITC (sparse GPs) inference is implemented. For a list of implemented covariance, mean, likelihood, and inference functions see list_of_functions.txt. The current implementation is optimized and tested, however, the work on this library is still in progress. We appreciate any feedback.

A comprehensive introduction to functionalities and demonstrations can be found in the doc folder; just open /doc/build/html/index.html in your browser to get to the html documentation of the whole package.

Further, pyGPs includes implementations of

  • implemented in python by Roland Memisevic 2008, following minimize.m which is copyright (C) 1999 - 2006, Carl Edward Rasmussen
  • (Copyright (c) Ian T Nabney (1996-2001))
  • (Copyright (c) by Hannes Nickisch 2010-01-10.)

Installing pyGPs

Download the archive and extract it to any local directory.

You can either add the local directory to your PYTHONPATH:

export PYTHONPATH=$PYTHONPATH:/path/to/local/directory/../parent_folder_of_pyGPs

or install the package using

python install

or install via pip::

pip install pyGPs 


  • python 2.6 or 2.7
  • scipy (v0.13.0 or later), numpy, and matplotlib: open-source packages for scientific computing using the Python programming language.


The following persons helped to improve this software: Roman Garnett, Maciej Kurek, Hannes Nickisch, Zhao Xu, and Alejandro Molina.

This work is partly supported by the Fraunhofer ATTRACT fellowship STREAM.

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