8 papers
A methodology for creating multidisciplinary design optimization benchmark problems from optimization ones
Matthias De Lozzo, Olivier Roustant, Amine Aziz-Alaoui
Benchmark problems with known solutions play a central role in the assessment of optimization algorithms. While mono-disciplinary optimization benefits from a rich collection of su…
Estimation and model errors in Gaussian-process-based Sensitivity Analysis of functional outputs
Yuri Taglieri Sáo, Olivier Roustant, Geraldo de Freitas Maciel
Global sensitivity analysis (GSA) of functional-output models is usually performed by combining statistical techniques, such as basis expansions, metamodeling and sampling based es…
Simulation of extreme functionals in meteoceanic data: Application to surge evolution over tidal cycles
Nathan Gorse, Olivier Roustant, Jérémy Rohmer +1
We investigate the influence of time-varying meteoceanic conditions on coastal flooding under the prism of rare events. Focusing on conditions observed over half tidal cycles, we o…
Non-asymptotic confidence regions on RKHS. The Paley-Wiener and standard Sobolev space cases
Fabrice Gamboa, Olivier Roustant
We consider the problem of constructing a global, probabilistic, and non-asymptotic confidence region for an unknown function observed on a random design. The unknown function is a…
General reproducing properties in RKHS with application to derivative and integral operators
Fatima-Zahrae El-Boukkouri, Josselin Garnier, Olivier Roustant
In this paper, we consider the reproducing property in Reproducing Kernel Hilbert Spaces (RKHS). We establish a reproducing property for the closure of the class of combinations of…
Block-Additive Gaussian Processes under Monotonicity Constraints
M. Deronzier, A. F. López-Lopera, F. Bachoc +2
We generalize the additive constrained Gaussian process framework to handle interactions between input variables while enforcing monotonicity constraints everywhere on the input sp…