21 citations · 46 across the 12 of their papers we have counts for
Showing 2022 · stat.MLShow all
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stat.ML2022★ 4 cited
What Can Be Learnt With Wide Convolutional Neural Networks?
Francesco Cagnetta, Alessandro Favero, Matthieu Wyart
Understanding how convolutional neural networks (CNNs) can efficiently learn high-dimensional functions remains a fundamental challenge. A popular belief is that these models harne…
stat.ML2022★ 6 cited
Learning sparse features can lead to overfitting in neural networks
Leonardo Petrini, Francesco Cagnetta, Eric Vanden-Eijnden +1
It is widely believed that the success of deep networks lies in their ability to learn a meaningful representation of the features of the data. Yet, understanding when and how this…