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Adaptive design of experiments for conservative estimation of excursion sets

2019, Azzimonti, Dario, Ginsbourger, David, Chevalier, Clément, Bect, Julien, Richet, Yann

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Estimating and quantifying uncertainties on level sets using the vorob’ev expectation and deviation with gaussian process models

2013, Chevalier, Clément, Ginsbourger, David, Bect, Julien, Molchanov, Ilya

Several methods based on Kriging have recently been proposed for calculating a probability of failure involving costly-to-evaluate functions. A closely related problem is to estimate the set of inputs leading to a response exceeding a given threshold. Now, estimating such a level set—and not solely its volume—and quantifying uncertainties on it are not straightforward. Here we use notions from random set theory to obtain an estimate of the level set, together with a quantification of estimation uncertainty. We give explicit formulae in the Gaussian process set-up and provide a consistency result. We then illustrate how space-filling versus adaptive design strategies may sequentially reduce level set estimation uncertainty.

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Quantifying uncertainties on excursion sets under a Gaussian random field prior

2016-8-2, Azzimonti, Dario, Bect, Julien, Chevalier, Clément, Ginsbourger, David

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Fast parallel kriging-based stepwise uncertainty reduction with application to the identification of an excursion set

2014, Chevalier, Clément, Bect, Julien, Ginsbourger, David, Vazquez, Emmanuel, Picheny, Victor, Richet, Yann