Active Learning Strategy for Surrogate-Based Quantile Estimation of Field Function

Active Learning Strategy for Surrogate-Based Quantile Estimation of Field Function

Uncertainty quantification is widely used in engineering domains to provide confidence measures on complex systems. It often requires to accurately estimate extreme statistics on computationally intensive black-box models. In case of spatially or temporally distributed model outputs, one valuable me...

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Bibliographic Details
Main Authors: Loïc Brevault, Mathieu Balesdent, Jorge-Luis Valderrama-Zapata
Format: Article
Language:English
Published: MDPI AG 2022-10-01
Series:Applied Sciences
Subjects:
active learning
quantile estimation
surrogate model
uncertainty quantification
stochastic process
Online Access:https://www.mdpi.com/2076-3417/12/19/10027

Internet

https://www.mdpi.com/2076-3417/12/19/10027

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