Publications associées à Surrogate model

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Analysis of the finite element heterogeneous multiscale method for quasilinear elliptic homogenization problems

Assyr Abdulle, Gilles Vilmart

A fully discrete analysis of the finite element heterogeneous multiscale method for a class of nonlinear elliptic homogenization problems of nonmonotone type is proposed. In contrast to previous results obtained for such problems in dimension

d\leq2

for ...

Amer Mathematical Soc2014

Surrogate model

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Self-learning surrogate models in superstructure optimization

Competing Adaptive Networks

Optimization Methods for Control: From Embedded Programmable Hardware to Data-Driven Process Optimization

Aerodynamic shape optimization via surrogate modelling with convolutional neural networks

Learning Non-Parametric Models with Guarantees: A Smooth Lipschitz Interpolation Approach

Machine learning methods to assist energy system optimization

On the Use of Transient Information for Static Real-Time Optimization

Integrating Rate Based Models into a Multi-Objective Process Design & Optimisation Framework using Surrogate Models

Analysis of the finite element heterogeneous multiscale method for quasilinear elliptic homogenization problems

KL-based Control of the Learning Schedule for Surrogate Black-Box Optimization

Optimization Methods for Control: From Embedded Programmable Hardware to Data-Driven Process Optimization

Competing Adaptive Networks

Analysis of the finite element heterogeneous multiscale method for quasilinear elliptic homogenization problems

Self-learning surrogate models in superstructure optimization

Learning Non-Parametric Models with Guarantees: A Smooth Lipschitz Interpolation Approach

Aerodynamic shape optimization via surrogate modelling with convolutional neural networks

Machine learning methods to assist energy system optimization

On the Use of Transient Information for Static Real-Time Optimization

Integrating Rate Based Models into a Multi-Objective Process Design & Optimisation Framework using Surrogate Models

KL-based Control of the Learning Schedule for Surrogate Black-Box Optimization