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2020 – today
- 2024
[j6]Simone Brivio, Stefania Fresca, Nicola Rares Franco, Andrea Manzoni
:
Error estimates for POD-DL-ROMs: a deep learning framework for reduced order modeling of nonlinear parametrized PDEs enhanced by proper orthogonal decomposition. Adv. Comput. Math. 50(3): 33 (2024)- [i17]Simone Brivio, Stefania Fresca, Andrea Manzoni:
PTPI-DL-ROMs: pre-trained physics-informed deep learning-based reduced order models for nonlinear parametrized PDEs. CoRR abs/2405.08558 (2024) - [i16]Nicola Farenga, Stefania Fresca, Simone Brivio, Andrea Manzoni:
On latent dynamics learning in nonlinear reduced order modeling. CoRR abs/2408.15183 (2024) - 2023
- [j5]Ludovica Cicci, Stefania Fresca, Mengwu Guo, Andrea Manzoni, Paolo Zunino:
Uncertainty quantification for nonlinear solid mechanics using reduced order models with Gaussian process regression. Comput. Math. Appl. 149: 1-23 (2023) - [j4]Nicola Rares Franco, Stefania Fresca, Andrea Manzoni, Paolo Zunino:
Approximation bounds for convolutional neural networks in operator learning. Neural Networks 161: 129-141 (2023) - [j3]Giorgio Gobat, Stefania Fresca, Andrea Manzoni, Attilio Frangi:
Reduced Order Modeling of Nonlinear Vibrating Multiphysics Microstructures with Deep Learning-Based Approaches. Sensors 23(6): 3001 (2023) - [i15]Ludovica Cicci, Stefania Fresca, Mengwu Guo, Andrea Manzoni, Paolo Zunino:
Uncertainty quantification for nonlinear solid mechanics using reduced order models with Gaussian process regression. CoRR abs/2302.08216 (2023) - [i14]Simone Brivio, Stefania Fresca, Nicola Rares Franco, Andrea Manzoni:
Error estimates for POD-DL-ROMs: a deep learning framework for reduced order modeling of nonlinear parametrized PDEs enhanced by proper orthogonal decomposition. CoRR abs/2305.04680 (2023) - [i13]Nicola Rares Franco, Stefania Fresca, Filippo Tombari, Andrea Manzoni:
Deep Learning-based surrogate models for parametrized PDEs: handling geometric variability through graph neural networks. CoRR abs/2308.01602 (2023) - 2022
- [j2]Ludovica Cicci, Stefania Fresca, Andrea Manzoni:
Deep-HyROMnet: A Deep Learning-Based Operator Approximation for Hyper-Reduction of Nonlinear Parametrized PDEs. J. Sci. Comput. 93(2): 57 (2022) - [i12]Federico Fatone, Stefania Fresca, Andrea Manzoni:
Long-time prediction of nonlinear parametrized dynamical systems by deep learning-based reduced order models. CoRR abs/2201.10215 (2022) - [i11]Ludovica Cicci, Stefania Fresca, Andrea Manzoni:
Deep-HyROMnet: A deep learning-based operator approximation for hyper-reduction of nonlinear parametrized PDEs. CoRR abs/2202.02658 (2022) - [i10]Ludovica Cicci, Stefania Fresca, Andrea Manzoni, Alfio Quarteroni:
Efficient approximation of cardiac mechanics through reduced order modeling with deep learning-based operator approximation. CoRR abs/2202.03904 (2022) - [i9]Giorgio Gobat, Stefania Fresca, Andrea Manzoni, Attilio Frangi:
Virtual twins of nonlinear vibrating multiphysics microstructures: physics-based versus deep learning-based approaches. CoRR abs/2205.05928 (2022) - [i8]Nicola Rares Franco, Stefania Fresca, Andrea Manzoni, Paolo Zunino:
Approximation bounds for convolutional neural networks in operator learning. CoRR abs/2207.01546 (2022) - [i7]Paolo Conti, Giorgio Gobat, Stefania Fresca, Andrea Manzoni, Attilio Frangi:
Reduced order modeling of parametrized systems through autoencoders and SINDy approach: continuation of periodic solutions. CoRR abs/2211.06786 (2022) - 2021
- [j1]Stefania Fresca, Luca Dedè, Andrea Manzoni:
A Comprehensive Deep Learning-Based Approach to Reduced Order Modeling of Nonlinear Time-Dependent Parametrized PDEs. J. Sci. Comput. 87(2): 61 (2021) - [i6]Stefania Fresca, Andrea Manzoni:
POD-DL-ROM: enhancing deep learning-based reduced order models for nonlinear parametrized PDEs by proper orthogonal decomposition. CoRR abs/2101.11845 (2021) - [i5]Stefania Fresca, Andrea Manzoni:
Real-time simulation of parameter-dependent fluid flows through deep learning-based reduced order models. CoRR abs/2106.05722 (2021) - [i4]Giorgio Gobat, Andrea Opreni, Stefania Fresca, Andrea Manzoni, Attilio Frangi:
Reduced order modeling of nonlinear microstructures through Proper Orthogonal Decomposition. CoRR abs/2109.12184 (2021) - [i3]Stefania Fresca, Giorgio Gobat, Patrick Fedeli, Attilio Frangi, Andrea Manzoni:
Deep learning-based reduced order models for the real-time simulation of the nonlinear dynamics of microstructures. CoRR abs/2111.12511 (2021) - 2020
- [i2]Stefania Fresca, Luca Dedè, Andrea Manzoni:
A comprehensive deep learning-based approach to reduced order modeling of nonlinear time-dependent parametrized PDEs. CoRR abs/2001.04001 (2020) - [i1]Stefania Fresca, Andrea Manzoni, Luca Dedè, Alfio Quarteroni:
Deep learning-based reduced order models in cardiac electrophysiology. CoRR abs/2006.03040 (2020)
Coauthor Index
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