Francesco Cagnetta

Publication Activity (10 Years)

Years Active: 2021-2024
Publications (10 Years): 12

Top Topics

Region Connection Calculus

Spatial Information

Top Venues

Mach. Learn. Sci. Technol.

Multim. Tools Appl.

Publications

Francesco Cagnetta, Matthieu Wyart
Towards a theory of how the structure of language is acquired by deep neural networks. CoRR (2024)
Umberto M. Tomasini, Leonardo Petrini, Francesco Cagnetta, Matthieu Wyart
How deep convolutional neural networks lose spatial information with training. Mach. Learn. Sci. Technol. 4 (4) (2023)
Francesco Cagnetta, Alessandro Favero, Matthieu Wyart
What Can Be Learnt With Wide Convolutional Neural Networks? ICML (2023)
Francesco Cagnetta, Deborah Oliveira, Mahalakshmi Sabanayagam, Nikolaos Tsilivis, Julia Kempe
Kernels, Data & Physics. CoRR (2023)
Leonardo Petrini, Francesco Cagnetta, Umberto M. Tomasini, Alessandro Favero, Matthieu Wyart
How Deep Neural Networks Learn Compositional Data: The Random Hierarchy Model. CoRR (2023)
Umberto M. Tomasini, Leonardo Petrini, Francesco Cagnetta, Matthieu Wyart
How deep convolutional neural networks lose spatial information with training. CoRR (2022)
Leonardo Petrini, Francesco Cagnetta, Eric Vanden-Eijnden, Matthieu Wyart
Learning sparse features can lead to overfitting in neural networks. NeurIPS (2022)
Francesco Cagnetta, Alessandro Favero, Matthieu Wyart
How Wide Convolutional Neural Networks Learn Hierarchical Tasks. CoRR (2022)
Leonardo Petrini, Francesco Cagnetta, Eric Vanden-Eijnden, Matthieu Wyart
Learning sparse features can lead to overfitting in neural networks. CoRR (2022)
Alessandro Favero, Francesco Cagnetta, Matthieu Wyart
Locality defeats the curse of dimensionality in convolutional teacher-student scenarios. CoRR (2021)
Maria Teresa Baldassarre, Danilo Caivano, Simone Romano, Francesco Cagnetta, Víctor Fernández-Cervantes, Eleni Stroulia
: a model-driven framework for generating exergames. Multim. Tools Appl. 80 (18) (2021)
Alessandro Favero, Francesco Cagnetta, Matthieu Wyart
Locality defeats the curse of dimensionality in convolutional teacher-student scenarios. NeurIPS (2021)