Search Results for author: Luca Dede

Found 1 papers, 0 papers with code

A comprehensive deep learning-based approach to reduced order modeling of nonlinear time-dependent parametrized PDEs

no code implementations12 Jan 2020 Stefania Fresca, Luca Dede, Andrea Manzoni

Traditional reduced order modeling techniques such as the reduced basis (RB) method (relying, e. g., on proper orthogonal decomposition (POD)) suffer from severe limitations when dealing with nonlinear time-dependent parametrized PDEs, because of the fundamental assumption of linear superimposition of modes they are based on.

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