Search Results for author: Francesca Bartolucci

Found 3 papers, 1 papers with code

Neural reproducing kernel Banach spaces and representer theorems for deep networks

no code implementations13 Mar 2024 Francesca Bartolucci, Ernesto de Vito, Lorenzo Rosasco, Stefano Vigogna

Studying the function spaces defined by neural networks helps to understand the corresponding learning models and their inductive bias.

Inductive Bias

Convolutional Neural Operators for robust and accurate learning of PDEs

2 code implementations NeurIPS 2023 Bogdan Raonić, Roberto Molinaro, Tim De Ryck, Tobias Rohner, Francesca Bartolucci, Rima Alaifari, Siddhartha Mishra, Emmanuel de Bézenac

Although very successfully used in conventional machine learning, convolution based neural network architectures -- believed to be inconsistent in function space -- have been largely ignored in the context of learning solution operators of PDEs.

Operator learning PDE Surrogate Modeling

Understanding neural networks with reproducing kernel Banach spaces

no code implementations20 Sep 2021 Francesca Bartolucci, Ernesto de Vito, Lorenzo Rosasco, Stefano Vigogna

Characterizing the function spaces corresponding to neural networks can provide a way to understand their properties.

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