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Conservative estimate for the excursion set of a deterministic function under a Gaussian random field model

Speaker: Dario Azzimonti (UniBern)

Abstract

The problem of estimating the excursion set of a deterministic function under a limited evaluation budget can be approached with Gaussian random field (GRF) modelling. Here we review two recent techniques based on Gaussian random field priors and we propose a fast algorithm to compute conservative estimates from the joint distribution of the posterior field.

Outline:

The role of model selection, summary statistics and multiple-point statistics in Bayesian inverse problems: Examples from geophysics.
A journey through Gaussian random fields with a view towards Bayesian optimization.
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