Francesco Cagnetta

According to our database, Francesco Cagnetta authored at least 8 papers between 2021 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

How deep convolutional neural networks lose spatial information with training.

Umberto M. Tomasini, Leonardo Petrini, Francesco Cagnetta, Matthieu Wyart

Mach. Learn. Sci. Technol., December, 2023

Kernels, Data & Physics.

Francesco Cagnetta, Deborah Oliveira, Mahalakshmi Sabanayagam, Nikolaos Tsilivis, Julia Kempe

CoRR, 2023

How Deep Neural Networks Learn Compositional Data: The Random Hierarchy Model.

Leonardo Petrini, Francesco Cagnetta, Umberto M. Tomasini, Alessandro Favero, Matthieu Wyart

CoRR, 2023

What Can Be Learnt With Wide Convolutional Neural Networks?

Francesco Cagnetta, Alessandro Favero, Matthieu Wyart

Proceedings of the International Conference on Machine Learning, 2023

2022

How Wide Convolutional Neural Networks Learn Hierarchical Tasks.

Francesco Cagnetta, Alessandro Favero, Matthieu Wyart

CoRR, 2022

Learning sparse features can lead to overfitting in neural networks.

Leonardo Petrini, Francesco Cagnetta, Eric Vanden-Eijnden, Matthieu Wyart

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

PhyDSL_K: a model-driven framework for generating exergames.

Maria Teresa Baldassarre, Danilo Caivano, Simone Romano, Francesco Cagnetta, Víctor Fernández-Cervantes, Eleni Stroulia

Multim. Tools Appl., 2021

Locality defeats the curse of dimensionality in convolutional teacher-student scenarios.

Alessandro Favero, Francesco Cagnetta, Matthieu Wyart

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021