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Research Program
New Software and Platforms
Bilateral Contracts and Grants with Industry
Bibliography
Research Program
New Software and Platforms
Bilateral Contracts and Grants with Industry
Bibliography


Section: New Results

Heteroskedastic Gaussian process modeling and sequential design

Participants : Mickaël Binois, Robert Gramacy [Virginia Tech] .

An increasing number of time-consuming simulators exhibit a complex noise structure that depends on the inputs. For conducting studies with limited budgets of evaluations, new surrogate methods are required in order to simultaneously model the mean and variance fields. To this end, in [43] we present the hetGP package https://cran.r-project.org/web/packages/hetGP, implementing many recent advances in Gaussian process modeling with input-dependent noise. First, we describe a simple, yet efficient, joint modeling framework that relies on replication for both speed and accuracy. Then we tackle the issue of data acquisition leveraging replication and exploration in a sequential manner for various goals, such as for obtaining a globally accurate model, for optimization, or for contour finding. Reproducible illustrations are provided throughout.