130 citations · 579 across the 34 of their papers we have counts for
4 papers · 1 filter
A staggered-in-time and non-conforming-in-space numerical framework for realistic cardiac electrophysiology outputs
Elena Zappon, Andrea Manzoni, Alfio Quarteroni
Computer-based simulations of non-invasive cardiac electrical outputs, such as electrocardiograms and body surface potential maps, usually entail severe computational costs due to…
Deep Learning-based surrogate models for parametrized PDEs: handling geometric variability through graph neural networks
Nicola Rares Franco, Stefania Fresca, Filippo Tombari +1
Mesh-based simulations play a key role when modeling complex physical systems that, in many disciplines across science and engineering, require the solution of parametrized time-de…
Error estimates for POD-DL-ROMs: a deep learning framework for reduced order modeling of nonlinear parametrized PDEs enhanced by proper orthogonal decomposition
Simone Brivio, Stefania Fresca, Nicola Rares Franco +1
POD-DL-ROMs have been recently proposed as an extremely versatile strategy to build accurate and reliable reduced order models (ROMs) for nonlinear parametrized partial differentia…
Uncertainty quantification for nonlinear solid mechanics using reduced order models with Gaussian process regression
Ludovica Cicci, Stefania Fresca, Mengwu Guo +2
Uncertainty quantification (UQ) tasks, such as sensitivity analysis and parameter estimation, entail a huge computational complexity when dealing with input-output maps involving t…