Nicola Rares Franco

20 papers Journal 20

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A short tour of operator learning theory: Convergence rates, statistical limits, and open questions. CoRR Simone Brugiapaglia, Nicola Rares Franco, Nicholas H. Nelsen
2026	J	`jnl`	Deep orthogonal decomposition: a continuously adaptive neural network approach to model order reduction of parametrized partial differential equations. Adv. Comput. Math. Nicola Rares Franco, Andrea Manzoni, Paolo Zunino, Jan S. Hesthaven
2026	J	`jnl`	Numerical solution of mixed-dimensional PDEs using a neural preconditioner. Comput. Math. Appl. Nunzio Dimola, Nicola Rares Franco, Paolo Zunino
2025	J	`jnl`	Deep Symmetric Autoencoders from the Eckart-Young-Schmidt Perspective. CoRR Simone Brivio, Nicola Rares Franco
2025	J	`jnl`	Nonparametric estimation of conditional probability distributions using a generative approach based on conditional push-forward neural networks. CoRR Nicola Rares Franco, Lorenzo Tedesco
2025	J	`jnl`	Numerical Solution of Mixed-Dimensional PDEs Using a Neural Preconditioner. CoRR Nunzio Dimola, Nicola Rares Franco, Paolo Zunino
2024	J	`jnl`	A practical existence theorem for reduced order models based on convolutional autoencoders. CoRR Nicola Rares Franco, Simone Brugiapaglia
2024	J	`jnl`	Deep learning enhanced cost-aware multi-fidelity uncertainty quantification of a computational model for radiotherapy. CoRR Piermario Vitullo, Nicola Rares Franco, Paolo Zunino
2024	J	`jnl`	Deep orthogonal decomposition: a continuously adaptive data-driven approach to model order reduction. CoRR Nicola Rares Franco, Andrea Manzoni, Paolo Zunino, Jan S. Hesthaven
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`	Measurability and continuity of parametric low-rank approximation in Hilbert spaces: linear operators and random variables. CoRR Nicola Rares Franco
2024	J	`jnl`	On the latent dimension of deep autoencoders for reduced order modeling of PDEs parametrized by random fields. Adv. Comput. Math. Nicola Rares Franco, Daniel Fraulin, Andrea Manzoni, Paolo Zunino
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`	Mesh-Informed Neural Networks for Operator Learning in Finite Element Spaces. J. Sci. Comput. Nicola Rares Franco, Andrea Manzoni, Paolo Zunino
2023	J	`jnl`	Nonlinear model order reduction for problems with microstructure using mesh informed neural networks. CoRR Piermario Vitullo, Alessio Colombo, Nicola Rares Franco, Andrea Manzoni, Paolo Zunino
2023	J	`jnl`	On the latent dimension of deep autoencoders for reduced order modeling of PDEs parametrized by random fields. CoRR Nicola Rares Franco, Daniel Fraulin, 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`	Learning Operators with Mesh-Informed Neural Networks. CoRR Nicola Rares Franco, Andrea Manzoni, Paolo Zunino