swh:1:snp:6298e170750eb9cfb13fbd6f84b11ca6a6738b27
Tip revision: 36230293422c6af5d956567162bba8c84a2f98ec authored by Rasmus Bonnevie on 02 August 2017, 15:43:05 UTC
Merge branch 'blockkernel' into fast-grad
Merge branch 'blockkernel' into fast-grad
Tip revision: 3623029
README.md
# GPflow
GPflow is a package for building Gaussian process models in python, using [TensorFlow](http://www.tensorflow.org). It was originally created and is now managed by [James Hensman](http://www.lancaster.ac.uk/staff/hensmanj/) and [Alexander G. de G. Matthews](http://mlg.eng.cam.ac.uk/?portfolio=alex-matthews).
The full list of [contributors](http://github.com/GPflow/GPflow/graphs/contributors) (in alphabetical order) is Rasmus Bonnevie, Alexis Boukouvalas, Ivo Couckuyt, Keisuke Fujii, Zoubin Ghahramani, David J. Harris, James Hensman, Pablo Leon-Villagra, Daniel Marthaler, Alexander G. de G. Matthews, Tom Nickson, Valentine Svensson and Mark van der Wilk. GPflow is an open source project so if you feel you have some relevant skills and are interested in contributing then please do contact us.
[![Python2.7 status](https://codeship.com/projects/26b43920-e96e-0133-3481-02cde9680eda/status?branch=master)](https://codeship.com/projects/147609)
[![Python3.5 Status](https://travis-ci.org/GPflow/GPflow.svg?branch=master)](https://travis-ci.org/GPflow/GPflow)
[![Coverage Status](http://codecov.io/github/GPflow/GPflow/coverage.svg?branch=master)](http://codecov.io/github/GPflow/GPflow?branch=master)
[![Documentation Status](https://readthedocs.org/projects/gpflow/badge/?version=latest)](http://gpflow.readthedocs.io/en/latest/?badge=latest)
# What does GPflow do?
GPflow implements modern Gaussian process inference for composable kernels and likelihoods. The [online user manual](http://gpflow.readthedocs.io/en/latest/) contains more details. The interface follows on from [GPy](http://github.com/sheffieldml/gpy), for more discussion of the comparison see [this page](http://gpflow.readthedocs.io/en/latest/intro.html#what-s-the-difference-between-gpy-and-gpflow).
# Install
## 1) Install TensorFlow.
Please see instructions on the main TensorFlow [webpage](https://www.tensorflow.org/versions/r0.12/get_started/os_setup.html#download-and-setup). You will need version 0.12. We find that for most users pip installation is the fastest way to get going.
## 2) install package
GPflow includes some tensorflow extensions that are compiled when you run setup.py. For those interested in modifying the source of GPflow, we recommend
```
python setup.py develop
```
but installation should work well too:
```
python setup.py install
```
You can run the tests with `python setup.py test`.
# Getting help
Please use gihub issues to start discussion on the use of GPflow. Tagging enquiries `discussion` helps us distinguish them from bugs.
# Contributing
All constuctive input is gratefully received. For more, see the [notes for contributors](contributing.md).
# Citing GPflow
To cite GPflow, please reference the [Technical report](https://arxiv.org/abs/1610.08733). Sample Bibtex is given below:
```
@ARTICLE{GPflow2016,
author = {Matthews, Alexander G. de G. and {van der Wilk}, Mark and Nickson, Tom and
Fujii, Keisuke. and {Boukouvalas}, Alexis and {Le{\'o}n-Villagr{\'a}}, Pablo and
Ghahramani, Zoubin and Hensman, James},
title = "{{GP}flow: A {G}aussian process library using {T}ensor{F}low}",
journal = {arXiv preprint 1610.08733},
year = 2016,
month = oct
}
```