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Conference papers
Integrating hyper-parameter uncertainties in a multi-fidelity Bayesian model for the estimation of a probability of failure
Abstract : A multi-fidelity simulator is a numerical model, in which one of the inputs controls a trade-off between the realism and the computational cost of the simulation. Our goal is to estimate the probability of exceeding a given threshold on a multi-fidelity stochastic simulator. We propose a fully Bayesian approach based on Gaussian processes to compute the posterior probability distribution of this probability. We pay special attention to the hyper-parameters of the model. Our methodology is illustrated on an academic example.
Cited literature [7 references]
https://hal-centralesupelec.archives-ouvertes.fr/hal-01590748
Contributor : Julien Bect <>
Submitted on : Wednesday, September 20, 2017 - 10:35:05 AM
Last modification on : Wednesday, April 8, 2020 - 3:50:28 PM
Contributor : Julien Bect <>
Submitted on : Wednesday, September 20, 2017 - 10:35:05 AM
Last modification on : Wednesday, April 8, 2020 - 3:50:28 PM
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AMCTM_STROH_article_2017.pdf
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