2 citations · 2 across the 1 of their papers we have counts for
2 papers
stat.CO2022★ 2 cited
Vecchia-approximated Deep Gaussian Processes for Computer Experiments
Annie Sauer, Andrew Cooper, Robert B. Gramacy
Deep Gaussian processes (DGPs) upgrade ordinary GPs through functional composition, in which intermediate GP layers warp the original inputs, providing flexibility to model non-sta…
stat.ME2020
Active Learning for Deep Gaussian Process Surrogates
Annie Sauer, Robert B. Gramacy, David Higdon
Deep Gaussian processes (DGPs) are increasingly popular as predictive models in machine learning (ML) for their non-stationary flexibility and ability to cope with abrupt regime ch…