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math.NA2020
A Comparison of Reduced-Order Modeling Approaches Using Artificial Neural Networks for PDEs with Bifurcating Solutions
Martin W. Hess, Annalisa Quaini, Gianluigi Rozza
This paper focuses on reduced-order models (ROMs) built for the efficient treatment of PDEs having solutions that bifurcate as the values of multiple input parameters change. First…
math.NA2020
MicroROM: An Efficient and Accurate Reduced Order Method to Solve Many-Query Problems in Micro-Motility
Nicola Giuliani, Martin W. Hess, Antonio DeSimone +1
In the study of micro-swimmers, both artificial and biological ones, many-query problems arise naturally. Even with the use of advanced high performance computing (HPC), it is not…