Scientific machine learning: methods to compute efficient surrogate models from small sets of observations - Di Fiore et al 2023a - Scipedia

10th Conference on Computational Methods in Marine Engineering (Marine 2023)

F. Di Fiore, P. Berri, L. Mainini

Abstract

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Published on 22/06/23
Submitted on 22/06/23

Volume Scientific Machine Learning and Reduced Order Modeling In Naval Engineering, 2023
DOI: 10.23967/marine.2023.111
Licence: CC BY-NC-SA license

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Keywords

Model Order Reduction • Scientific Machine Learning • Statistical Learning • Surrogate modelling

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