324 citations · 484 across the 31 of their papers we have counts for
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Additive Covariance Kernels for High-Dimensional Gaussian Process Modeling
Nicolas Durrande, David Ginsbourger, Olivier Roustant +1
Gaussian process models -also called Kriging models- are often used as mathematical approximations of expensive experiments. However, the number of observation required for buildin…
ANOVA kernels and RKHS of zero mean functions for model-based sensitivity analysis
Nicolas Durrande, David Ginsbourger, Olivier Roustant +1
Given a reproducing kernel Hilbert space H of real-valued functions and a suitable measure mu over the source space D (subset of R), we decompose H as the sum of a subspace of cent…
Additive Kernels for Gaussian Process Modeling
Nicolas Durrande, David Ginsbourger, Olivier Roustant
Gaussian Process (GP) models are often used as mathematical approximations of computationally expensive experiments. Provided that its kernel is suitably chosen and that enough dat…