fvGP - A Flexible Multi-Task GP Engine
Welcome to the documentation of the fvGP API.
fvGP is a next-generation Gaussian (and Gaussian-related) process engine for flexible, domain-informed and HPC-ready stochastic function approximation. It is the backbone of the gpCAM API. The objective of fvGP is to take care of the mathematics behind GP training and predictions but allow the user to have maximum flexibility in defining GPs. The fv in fvGP stands for function valued, an extension of multi-task GPs by the notion of an output space with it’s own topology. In this framwork, the output space is assumed to have a non-constant (accoss input and output space) metric for the norm that can be learned via hyperparameter optimization. HGDL provides distributed multi-node asynchronous constrained function optimization for the training.
The fvGP package holds the world record for scaling up exact GPs!