Machine Learning for Scientific Computing and Numerical Analysis

Abstract

MasterThis MSc course introduces and develops advanced methods at the intersection of machine learning and scientific computing, with a special emphasis on solving and analyzing forward and inverse problems governed by partial differential equations. Students will learn how to combine classical numerical methods with modern neural-network architectures to approximate functions, operators, and solution maps, while critically assessing stability, generalization, and interpretability

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Last time updated on 26/05/2026

This paper was published in Portail HAL edf.

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Licence: info:eu-repo/semantics/OpenAccess