Reduction, Approximation, Machine Learning, Surrogates, Emulators and Simulators

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Reduction, Approximation, Machine Learning, Surrogates, Emulators and Simulators is written by Gianluigi Rozza and published by Springer Nature. It's available with International Standard Book Number or ISBN identification 3031550609 (ISBN 10) and 9783031550607 (ISBN 13).

This volume is focused on the review of recent algorithmic and mathematical advances and the development of new research directions for Mathematical Model Approximations via RAMSES (Reduced order models, Approximation theory, Machine learning, Surrogates, Emulators, Simulators) in the setting of parametrized partial differential equations also with sparse and noisy data in high-dimensional parameter spaces. The book is a valuable resource for researchers, as well as masters and Ph.D students.