Stefania Fresca

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 22

Top Topics

Nonlinear Dynamics

Gaussian Process Regression

Convolutional Neural Networks

Top Venues

J. Sci. Comput.

Comput. Math. Appl.

Publications

Simone Brivio, Stefania Fresca, Andrea Manzoni
PTPI-DL-ROMs: pre-trained physics-informed deep learning-based reduced order models for nonlinear parametrized PDEs. CoRR (2024)
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) (2024)
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 (2023)
Giorgio Gobat, Stefania Fresca, Andrea Manzoni, Attilio Frangi
Reduced Order Modeling of Nonlinear Vibrating Multiphysics Microstructures with Deep Learning-Based Approaches. Sensors 23 (6) (2023)
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 (2023)
Nicola Rares Franco, Stefania Fresca, Andrea Manzoni, Paolo Zunino
Approximation bounds for convolutional neural networks in operator learning. Neural Networks 161 (2023)
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 (2023)
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 (2023)
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 (2022)
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) (2022)
Federico Fatone, Stefania Fresca, Andrea Manzoni
Long-time prediction of nonlinear parametrized dynamical systems by deep learning-based reduced order models. CoRR (2022)
Ludovica Cicci, Stefania Fresca, Andrea Manzoni
Deep-HyROMnet: A deep learning-based operator approximation for hyper-reduction of nonlinear parametrized PDEs. CoRR (2022)
Giorgio Gobat, Stefania Fresca, Andrea Manzoni, Attilio Frangi
Virtual twins of nonlinear vibrating multiphysics microstructures: physics-based versus deep learning-based approaches. CoRR (2022)
Ludovica Cicci, Stefania Fresca, Andrea Manzoni, Alfio Quarteroni
Efficient approximation of cardiac mechanics through reduced order modeling with deep learning-based operator approximation. CoRR (2022)
Nicola Rares Franco, Stefania Fresca, Andrea Manzoni, Paolo Zunino
Approximation bounds for convolutional neural networks in operator learning. CoRR (2022)
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 (2021)
Giorgio Gobat, A. Opreni, Stefania Fresca, Andrea Manzoni, Attilio Frangi
Reduced order modeling of nonlinear microstructures through Proper Orthogonal Decomposition. CoRR (2021)
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) (2021)
Stefania Fresca, Andrea Manzoni
Real-time simulation of parameter-dependent fluid flows through deep learning-based reduced order models. CoRR (2021)
Stefania Fresca, Andrea Manzoni
POD-DL-ROM: enhancing deep learning-based reduced order models for nonlinear parametrized PDEs by proper orthogonal decomposition. CoRR (2021)
Stefania Fresca, Andrea Manzoni, Luca Dedè, Alfio Quarteroni
Deep learning-based reduced order models in cardiac electrophysiology. CoRR (2020)
Stefania Fresca, Luca Dedè, Andrea Manzoni
A comprehensive deep learning-based approach to reduced order modeling of nonlinear time-dependent parametrized PDEs. CoRR (2020)