Notice: Please be sure to update your copy of Torch7 prior to work with gpTorch7.

# gpTorch7 # __gpTorch7__ is a framework for Gaussian Process-based machine learning implemented in Torch7. For it's companion package on Bayesian Optimization, please refer to [bot7](https://github.com/j-wilson/bot7). This package is currently still in an alpha-build stage; so, please feel free to pass along suggestions and/or feedback. ## Package Content ##

Directory	Content
models	Gaussian Process models
kernels	Covariance functions / Noise models
means	Mean functions
samplers	Sampling methods (e.g. slice sampling)
examples	Demos

Installation and Usage

You can install gpTorch7 via luarocks provided by the torch distribution.

git clone https://github.com/j-wilson/gpTorch7
cd gpTorch7
luarocks make

After installing gp, you can load the package inside Torch via:

require('gp');
th> gpTorch7.
gpTorch7.means.       gpTorch7.samplers.   gpTorch7.kernels.     
gpTorch7.models.      gpTorch7.utils.

Developers' Notes

Further documentation coming soon.