6 citations · 6 across the 1 of their papers we have counts for
5 papers
Modeling non-stationary extreme dependence with stationary max-stable processes and multidimensional scaling
Clément Chevalier, David Ginsbourger, Olivia Martius
Modeling the joint distribution of extreme weather events in multiple locations is a challenging task with important applications. In this study, we use max-stable models to study…
Properties and comparison of some Kriging sub-model aggregation methods
François Bachoc, Nicolas Durrande, Didier Rullière +1
Kriging is a widely employed technique, in particular for computer experiments, in machine learning or in geostatistics. An important challenge for Kriging is the computational bur…
Adaptive Design of Experiments for Conservative Estimation of Excursion Sets
Dario Azzimonti, David Ginsbourger, Clément Chevalier +2
We consider the problem of estimating the set of all inputs that leads a system to some particular behavior. The system is modeled by an expensive-to-evaluate function, such as a c…
Efficient batch-sequential Bayesian optimization with moments of truncated Gaussian vectors
Sébastien Marmin, Clément Chevalier, David Ginsbourger
We deal with the efficient parallelization of Bayesian global optimization algorithms, and more specifically of those based on the expected improvement criterion and its variants.…
Nested Kriging predictions for datasets with large number of observations
Didier Rullière, Nicolas Durrande, François Bachoc +1
This work falls within the context of predicting the value of a real function at some input locations given a limited number of observations of this function. The Kriging interpola…