Deep learning-based reduced order models in cardiac electrophysiology. - Stefania Fresca; Andrea Manzoni; Luca Dedè; Alfio Quarteroni (CoRR, 2020)

POD-DL-ROM: enhancing deep learning-based reduced order models for nonlinear parametrized PDEs by proper orthogonal decomposition. - Stefania Fresca; Andrea Manzoni (CoRR, 2021)

Real-time simulation of parameter-dependent fluid flows through deep learning-based reduced order models. - Stefania Fresca; Andrea Manzoni (CoRR, 2021)

Reduced order modeling of nonlinear microstructures through Proper Orthogonal Decomposition. - Giorgio Gobat; Andrea Opreni; Stefania Fresca; Andrea Manzoni; Attilio Frangi (CoRR, 2021)

Deep learning-based reduced order models for the real-time simulation of the nonlinear dynamics of microstructures. - Stefania Fresca; Giorgio Gobat; Patrick Fedeli; Attilio Frangi; Andrea Manzoni (CoRR, 2021)

A Comprehensive Deep Learning-Based Approach to Reduced Order Modeling of Nonlinear Time-Dependent Parametrized PDEs. - Stefania Fresca; Luca Dedè; Andrea Manzoni (J. Sci. Comput., 2021)

Long-time prediction of nonlinear parametrized dynamical systems by deep learning-based reduced order models. - Federico Fatone; Stefania Fresca; Andrea Manzoni (CoRR, 2022)

Efficient approximation of cardiac mechanics through reduced order modeling with deep learning-based operator approximation. - Ludovica Cicci; Stefania Fresca; Andrea Manzoni; Alfio Quarteroni (CoRR, 2022)

Virtual twins of nonlinear vibrating multiphysics microstructures: physics-based versus deep learning-based approaches. - Giorgio Gobat; Stefania Fresca; Andrea Manzoni; Attilio Frangi (CoRR, 2022)

Reduced order modeling of parametrized systems through autoencoders and SINDy approach: continuation of periodic solutions. - Paolo Conti; Giorgio Gobat; Stefania Fresca; Andrea Manzoni; Attilio Frangi (CoRR, 2022)

Deep-HyROMnet: A Deep Learning-Based Operator Approximation for Hyper-Reduction of Nonlinear Parametrized PDEs. - Ludovica Cicci; Stefania Fresca; Andrea Manzoni (J. Sci. Comput., 2022)

Deep Learning-based surrogate models for parametrized PDEs: handling geometric variability through graph neural networks. - Nicola Rares Franco; Stefania Fresca; Filippo Tombari; Andrea Manzoni (CoRR, 2023)

Reduced Order Modeling of Nonlinear Vibrating Multiphysics Microstructures with Deep Learning-Based Approaches. - Giorgio Gobat; Stefania Fresca; Andrea Manzoni; Attilio Frangi (Sensors, 2023)

Approximation bounds for convolutional neural networks in operator learning. - Nicola Rares Franco; Stefania Fresca; Andrea Manzoni; Paolo Zunino (Neural Networks, 2023)

Uncertainty quantification for nonlinear solid mechanics using reduced order models with Gaussian process regression. - Ludovica Cicci; Stefania Fresca; Mengwu Guo; Andrea Manzoni; Paolo Zunino (Comput. Math. Appl., 2023)

PTPI-DL-ROMs: pre-trained physics-informed deep learning-based reduced order models for nonlinear parametrized PDEs. - Simone Brivio; Stefania Fresca; Andrea Manzoni (CoRR, 2024)

Handling geometrical variability in nonlinear reduced order modeling through Continuous Geometry-Aware DL-ROMs. - Simone Brivio; Stefania Fresca; Andrea Manzoni (CoRR, 2024)

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; Andrea Manzoni (Adv. Comput. Math., 2024)

On latent dynamics learning in nonlinear reduced order modeling. - Nicola Farenga; Stefania Fresca; Simone Brivio; Andrea Manzoni (Neural Networks, 2025)

HypeRL: Parameter-Informed Reinforcement Learning for Parametric PDEs. - Nicolò Botteghi; Stefania Fresca; Mengwu Guo; Andrea Manzoni (CoRR, 2025)

Beyond Interpolation: Extrapolative Reasoning with Reinforcement Learning and Graph Neural Networks. - Niccolò Grillo; Andrea Toccaceli; Joël Mathys; Benjamin Estermann; Stefania Fresca; Roger Wattenhofer (CoRR, 2025)

Integrating Fourier Neural Operators with Diffusion Models to improve Spectral Representation of Synthetic Earthquake Ground Motion Response. - Niccolò Perrone; Fanny Lehmann; Hugo Gabrielidis; Stefania Fresca; Filippo Gatti (CoRR, 2025)

Multi-Level Monte Carlo Training of Neural Operators. - James Rowbottom; Stefania Fresca; Pietro Lio; Carola-Bibiane Schönlieb; Nicolas Boullé (CoRR, 2025)