Reduction, Approximation, Machine Learning, Surrogates, Emulators and Simulators
RAMSES
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Beschreibung
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.
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.
Provides guidelines for the most promising approaches for near-future research Synergistic exchanges between the mathematics and data science communities Latest knowledge and results on emerging topics
Autor*in
Gianluigi Rozza
Themen in »Reduction, Approximation, Machine Learning, Surrogates, Emulators and Simulators«
Model order reduction Machine learning Approximation of PDEs Surrogates Emulators Simulators