Fast emulation of density functional theory simulations using approximate Gaussian processes

no code implementations • 24 Aug 2022 • Steven Stetzler, Michael Grosskopf, Earl Lawrence

This work examines the accuracy-runtime trade-off of several approximate Gaussian process models -- the sparse variational GP, stochastic variational GP, and deep kernel learned GP -- when emulating the predictions of density functional theory (DFT) models.

Gaussian Processes