fvGP — A Flexible Multi-Task GP Engine#
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 handle the mathematics behind GP training and predictions while giving the user maximum flexibility in defining kernels, mean functions, and noise models. The fv in fvGP stands for function-valued — an extension of multi-task GPs by the notion of an output space with its own topology, whose metric can be learned via hyperparameter optimization. HGDL provides distributed multi-node asynchronous constrained optimization for training.
The fvGP package holds the world record for scaling up exact GPs!