Stefania Fresca

31 papers Journal 31

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Beyond Interpolation: Extrapolative Reasoning with Reinforcement Learning and Graph Neural Networks. CoRR Niccolò Grillo, Andrea Toccaceli, Joël Mathys, Benjamin Estermann, Stefania Fresca, Roger Wattenhofer
2025	J	`jnl`	Explainable Deep Learning-based Classification of Wolff-Parkinson-White Electrocardiographic Signals. CoRR Alice Ragonesi, Stefania Fresca, Karli Gillette, Stefan Kurath-Koller, Gernot Plank, Elena Zappon
2025	J	`jnl`	HypeR Adaptivity: Joint CoRR Niccolò Grillo, James Rowbottom, Pietro Liò, Carola-Bibiane Schönlieb, Stefania Fresca
2025	J	`jnl`	HypeRL: Parameter-Informed Reinforcement Learning for Parametric PDEs. CoRR Nicolò Botteghi, Stefania Fresca, Mengwu Guo, Andrea Manzoni
2025	J	`jnl`	Integrating Fourier Neural Operators with Diffusion Models to improve Spectral Representation of Synthetic Earthquake Ground Motion Response. CoRR Niccolò Perrone, Fanny Lehmann, Hugo Gabrielidis, Stefania Fresca, Filippo Gatti
2025	J	`jnl`	Multi-Level Monte Carlo Training of Neural Operators. CoRR James Rowbottom, Stefania Fresca, Pietro Lio, Carola-Bibiane Schönlieb, Nicolas Boullé
2025	J	`jnl`	On latent dynamics learning in nonlinear reduced order modeling. Neural Networks Nicola Farenga, Stefania Fresca, Simone Brivio, Andrea Manzoni
2024	J	`jnl`	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. Simone Brivio, Stefania Fresca, Nicola Rares Franco, Andrea Manzoni
2024	J	`jnl`	Handling geometrical variability in nonlinear reduced order modeling through Continuous Geometry-Aware DL-ROMs. CoRR Simone Brivio, Stefania Fresca, Andrea Manzoni
2024	J	`jnl`	On latent dynamics learning in nonlinear reduced order modeling. CoRR Nicola Farenga, Stefania Fresca, Simone Brivio, Andrea Manzoni
2024	J	`jnl`	PTPI-DL-ROMs: pre-trained physics-informed deep learning-based reduced order models for nonlinear parametrized PDEs. CoRR Simone Brivio, Stefania Fresca, Andrea Manzoni
2023	J	`jnl`	Approximation bounds for convolutional neural networks in operator learning. Neural Networks Nicola Rares Franco, Stefania Fresca, Andrea Manzoni, Paolo Zunino
2023	J	`jnl`	Deep Learning-based surrogate models for parametrized PDEs: handling geometric variability through graph neural networks. CoRR Nicola Rares Franco, Stefania Fresca, Filippo Tombari, Andrea Manzoni
2023	J	`jnl`	Error estimates for POD-DL-ROMs: a deep learning framework for reduced order modeling of nonlinear parametrized PDEs enhanced by proper orthogonal decomposition. CoRR Simone Brivio, Stefania Fresca, Nicola Rares Franco, Andrea Manzoni
2023	J	`jnl`	Reduced Order Modeling of Nonlinear Vibrating Multiphysics Microstructures with Deep Learning-Based Approaches. Sensors Giorgio Gobat, Stefania Fresca, Andrea Manzoni, Attilio Frangi
2023	J	`jnl`	Uncertainty quantification for nonlinear solid mechanics using reduced order models with Gaussian process regression. Comput. Math. Appl. Ludovica Cicci, Stefania Fresca, Mengwu Guo, Andrea Manzoni, Paolo Zunino
2023	J	`jnl`	Uncertainty quantification for nonlinear solid mechanics using reduced order models with Gaussian process regression. CoRR Ludovica Cicci, Stefania Fresca, Mengwu Guo, Andrea Manzoni, Paolo Zunino
2022	J	`jnl`	Approximation bounds for convolutional neural networks in operator learning. CoRR Nicola Rares Franco, Stefania Fresca, Andrea Manzoni, Paolo Zunino
2022	J	`jnl`	Deep-HyROMnet: A Deep Learning-Based Operator Approximation for Hyper-Reduction of Nonlinear Parametrized PDEs. J. Sci. Comput. Ludovica Cicci, Stefania Fresca, Andrea Manzoni
2022	J	`jnl`	Deep-HyROMnet: A deep learning-based operator approximation for hyper-reduction of nonlinear parametrized PDEs. CoRR Ludovica Cicci, Stefania Fresca, Andrea Manzoni
2022	J	`jnl`	Efficient approximation of cardiac mechanics through reduced order modeling with deep learning-based operator approximation. CoRR Ludovica Cicci, Stefania Fresca, Andrea Manzoni, Alfio Quarteroni
2022	J	`jnl`	Long-time prediction of nonlinear parametrized dynamical systems by deep learning-based reduced order models. CoRR Federico Fatone, Stefania Fresca, Andrea Manzoni
2022	J	`jnl`	Reduced order modeling of parametrized systems through autoencoders and SINDy approach: continuation of periodic solutions. CoRR Paolo Conti, Giorgio Gobat, Stefania Fresca, Andrea Manzoni, Attilio Frangi
2022	J	`jnl`	Virtual twins of nonlinear vibrating multiphysics microstructures: physics-based versus deep learning-based approaches. CoRR Giorgio Gobat, Stefania Fresca, Andrea Manzoni, Attilio Frangi
2021	J	`jnl`	A Comprehensive Deep Learning-Based Approach to Reduced Order Modeling of Nonlinear Time-Dependent Parametrized PDEs. J. Sci. Comput. Stefania Fresca, Luca Dedè, Andrea Manzoni
2021	J	`jnl`	Deep learning-based reduced order models for the real-time simulation of the nonlinear dynamics of microstructures. CoRR Stefania Fresca, Giorgio Gobat, Patrick Fedeli, Attilio Frangi, Andrea Manzoni
2021	J	`jnl`	POD-DL-ROM: enhancing deep learning-based reduced order models for nonlinear parametrized PDEs by proper orthogonal decomposition. CoRR Stefania Fresca, Andrea Manzoni
2021	J	`jnl`	Real-time simulation of parameter-dependent fluid flows through deep learning-based reduced order models. CoRR Stefania Fresca, Andrea Manzoni
2021	J	`jnl`	Reduced order modeling of nonlinear microstructures through Proper Orthogonal Decomposition. CoRR Giorgio Gobat, Andrea Opreni, Stefania Fresca, Andrea Manzoni, Attilio Frangi
2020	J	`jnl`	A comprehensive deep learning-based approach to reduced order modeling of nonlinear time-dependent parametrized PDEs. CoRR Stefania Fresca, Luca Dedè, Andrea Manzoni
2020	J	`jnl`	Deep learning-based reduced order models in cardiac electrophysiology. CoRR Stefania Fresca, Andrea Manzoni, Luca Dedè, Alfio Quarteroni