jomorlier

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Professor in Structural and Multidisciplinary Design Optimization

ISAE-SUPAERO / ICA CNRS

SMT: The Surrogate Modeling Toolbox with ONERA, NASA and University Of Michigan

LinkedIn Network Artificial Intelligence for Engineering

Academic Partner of MonolithAI

Approximate inference in related multi-output Gaussian Process Regression

In Gaussian Processes a multi-output kernel is a covariance function ove...
11/18/2020 ∙ by jomorlier , et al. ∙ 0 ∙ share

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Adaptive modeling strategy for constrained global optimization with application to aerodynamic wing design

Surrogate models are often used to reduce the cost of design optimizatio...
11/18/2020 ∙ by jomorlier , et al. ∙ 0 ∙ share

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Efficient global optimization for high-dimensional constrained problems by using the Kriging models combined with the partial least squares method

In many engineering optimization problems, the number of function evalua...
11/18/2020 ∙ by jomorlier , et al. ∙ 0 ∙ share

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Surrogate modeling approximation using a mixture of experts based on EM joint estimation

An automatic method to combine several local surrogate models is present...
11/18/2020 ∙ by jomorlier , et al. ∙ 0 ∙ share

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Improving kriging surrogates of high-dimensional design models by Partial Least Squares dimension reduction

Engineering computer codes are often computationally expensive. To light...
11/18/2020 ∙ by jomorlier , et al. ∙ 0 ∙ share

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A Python surrogate modeling framework with derivatives

The surrogate modeling toolbox (SMT) is an open-source Python package co...
11/18/2020 ∙ by jomorlier , et al. ∙ 0 ∙ share

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