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Stefania Fresca
Stefania Fresca
MOX - Dipartimento di Matematica, Politecnico di Milano
Email verificata su polimi.it - Home page
Titolo
Citata da
Citata da
Anno
A comprehensive deep learning-based approach to reduced order modeling of nonlinear time-dependent parametrized PDEs
S Fresca, L Dede’, A Manzoni
Journal of Scientific Computing 87, 1-36, 2021
2732021
POD-DL-ROM: enhancing deep learning-based reduced order models for nonlinear parametrized PDEs by proper orthogonal decomposition
S Fresca, A Manzoni
Computer Methods in Applied Mechanics and Engineering 388, 114181, 2022
2452022
Deep learning-based reduced order models in cardiac electrophysiology
S Fresca, A Manzoni, L Dedè, A Quarteroni
PLOS ONE 15 (10), 1-32, 2020
772020
Real-time simulation of parameter-dependent fluid flows through deep learning-based reduced order models
S Fresca, A Manzoni
Fluids 6 (7), 2021
472021
POD-Enhanced Deep Learning-Based Reduced Order Models for the Real-Time Simulation of Cardiac Electrophysiology in the Left Atrium
S Fresca, A Manzoni, L Dedè, A Quarteroni
Frontiers in physiology, 1431, 2021
462021
Reduced order modeling of parametrized systems through autoencoders and SINDy approach: continuation of periodic solutions
P Conti, G Gobat, S Fresca, A Manzoni, A Frangi
Computer Methods in Applied Mechanics and Engineering 411, 116072, 2023
432023
Deep learning‐based reduced order models for the real‐time simulation of the nonlinear dynamics of microstructures
S Fresca, G Gobat, P Fedeli, A Frangi, A Manzoni
International Journal for Numerical Methods in Engineering 123 (20), 4749-4777, 2022
352022
Reduced order modeling of nonlinear microstructures through proper orthogonal decomposition
G Gobat, A Opreni, S Fresca, A Manzoni, A Frangi
Mechanical Systems and Signal Processing 171, 108864, 2022
332022
Deep-HyROMnet: A deep learning-based operator approximation for hyper-reduction of nonlinear parametrized PDEs
L Cicci, S Fresca, A Manzoni
Journal of Scientific Computing 93 (2), 57, 2022
302022
Approximation bounds for convolutional neural networks in operator learning
NR Franco, S Fresca, A Manzoni, P Zunino
Neural Networks 161, 129-141, 2023
252023
Efficient approximation of cardiac mechanics through reduced‐order modeling with deep learning‐based operator approximation
L Cicci, S Fresca, A Manzoni, A Quarteroni
International Journal for Numerical Methods in Biomedical Engineering 40 (1 …, 2024
182024
Uncertainty quantification for nonlinear solid mechanics using reduced order models with Gaussian process regression
L Cicci, S Fresca, M Guo, A Manzoni, P Zunino
Computers & Mathematics with Applications 149, 1-23, 2023
152023
Long-time prediction of nonlinear parametrized dynamical systems by deep learning-based reduced order models
S Fresca, F Fatone, A Manzoni
Mathematics in Engineering 5 (6), 1-36, 2023
15*2023
Deep learning-based surrogate models for parametrized PDEs: Handling geometric variability through graph neural networks
NR Franco, S Fresca, F Tombari, A Manzoni
Chaos: An Interdisciplinary Journal of Nonlinear Science 33 (12), 2023
142023
Error estimates for POD-DL-ROMs: a deep learning framework for reduced order modeling of nonlinear parametrized PDEs enhanced by proper orthogonal decomposition
S Brivio, S Fresca, NR Franco, A Manzoni
Advances in Computational Mathematics 50 (3), 33, 2024
122024
Projection-based reduced order models for parameterized nonlinear time-dependent problems arising in cardiac mechanics
L Cicci, S Fresca, S Pagani, A Manzoni, A Quarteroni
Mathematics in Engineering 5 (2), 1-38, 2023
122023
Reduced order modeling of nonlinear vibrating multiphysics microstructures with deep learning-based approaches
G Gobat, S Fresca, A Manzoni, A Frangi
Sensors 23 (6), 3001, 2023
102023
Modelling the Periodic Response of Micro-Electromechanical Systems through Deep Learning-Based Approaches
G Gobat, A Baronchelli, S Fresca, A Frangi
Actuators 12 (7), 278, 2023
32023
Long-time prediction of nonlinear parametrized dynamical systems by deep learning-based ROMs
S Fresca, F Fatone, A Manzoni
The Symbiosis of Deep Learning and Differential Equations, 2021
32021
PTPI-DL-ROMs: pre-trained physics-informed deep learning-based reduced order models for nonlinear parametrized PDEs
S Brivio, S Fresca, A Manzoni
arXiv preprint arXiv:2405.08558, 2024
22024
Il sistema al momento non può eseguire l'operazione. Riprova più tardi.
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