FEREBUS: a high-performance modern Gaussian process regression engine
Matthew J. Burn, Paul L. A. Popelier
Abstract
FEREBUS is a highly optimised Gaussian process regression (GPR) engine, which provides both model and optimiser flexibility to produce tailored models designed for domain specific applications.
Topics & Concepts
RegressionProcess (computing)Gaussian processKrigingComputer scienceStatisticsMathematicsMachine learningGaussianOperating systemPhysicsQuantum mechanicsMachine Learning in Materials ScienceMass Spectrometry Techniques and ApplicationsGaussian Processes and Bayesian Inference