Estimation of Small Quantile Sets Using a Sequential Bayesian Strategy - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2024

Estimation of Small Quantile Sets Using a Sequential Bayesian Strategy

Résumé

Given a numerical simulator of a physical phenomenon or system, one often seeks to determine the set of inputs that lead to values with specified properties. This type of problem, broadly known as "set inversion," has several variants, depending on the properties sought for the outputs. In this communication, we concentrate on a specific robust set inversion problem termed “quantile set inversion" (QSI). In this context, the function of interest has both deterministic and uncertain inputs. The objective within this framework is to estimate the set of deterministic inputs so that the probability—with respect to the distribution of the uncertain inputs—of the output variables falling within a given range is below a given threshold. To address this problem, we recently proposed (Ait Abdelmalek-Lomenech, Bect, Chabridon & Vazquez, arXiv:2211.01008v2, 2023) a sequential Bayesian sampling strategy based on the Stepwise Uncertainty Reduction (SUR) principle. We now suggest an adaptation of this method, employing sequential Monte Carlo (SMC) sampling, to tackle cases where the set to be estimated is small compared to the full domain of deterministic inputs.
raal-siamuq24.pdf (1.36 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-04501097 , version 1 (12-03-2024)

Licence

Paternité - Pas d'utilisation commerciale - Pas de modification

Identifiants

  • HAL Id : hal-04501097 , version 1

Citer

Romain Ait Abdelmalek-Lomenech, Julien Bect, Vincent Chabridon, Emmanuel Vazquez. Estimation of Small Quantile Sets Using a Sequential Bayesian Strategy. SIAM Conference on Uncertainty Quantification (UQ24), Feb 2024, Trieste, Italy. ⟨hal-04501097⟩
5 Consultations
4 Téléchargements

Partager

Gmail Facebook X LinkedIn More