juliet — juliet documentation
User Guide
George is a fast and flexible Python library for Gaussian Process (GP) Regression. A full introduction to the theory of Gaussian Processes is beyond the scope of this documentation but the best resource is available for free online: Rasmussen & Williams (2006) .
Unlike some other GP implementations, george is focused on efficiently evaluating the marginalized likelihood of a dataset under a GP prior, even as this dataset gets Big™. As you’ll see in these pages of documentation, the module exposes quite a few other features but it is designed to be used alongside your favorite non-linear optimization or posterior inference library for the best results.
juliet — juliet documentation