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ANOVA kernels and RKHS of zero mean functions for model-based sensitivity ana...
International audience -
Regularity dependence of the rate of convergence of the learning curve for Ga...
This paper deals with the speed of convergence of the learning curve in a Gaussian process regression framework. The learning curve describes the average... -
Asymptotic normality of a Sobol index estimator in Gaussian process regressio...
Stochastic simulators such as Monte-Carlo estimators are widely used in science and engineering to study physical systems through their probabilistic representation.... -
A Bayesian approach for global sensitivity analysis of (multi-fidelity) compu...
International audience -
Multi-fidelity Gaussian process regression for computer experiments
This work is on Gaussian-process based approximation of a code which can be run at different levels of accuracy. The goal is to improve the predictions of a surrogate... -
ANOVA decomposition of conditional Gaussian processes for sensitivity analysi...
International audience
