6 citations · 8 across the 3 of their papers we have counts for
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stat.CO2025
Modernizing full posterior inference for surrogate modeling of categorical-output simulation experiments
Andrew Cooper, Annie S. Booth, Robert B. Gramacy
Gaussian processes (GPs) are powerful tools for nonlinear classification in which latent GPs are combined with link functions. But GPs do not scale well to large training data. Thi…
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…