Stefano Spigler

According to our database, Stefano Spigler authored at least 8 papers between 2018 and 2021.

Collaborative distances:

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

2021

How isotropic kernels perform on simple invariants.

Jonas Paccolat, Stefano Spigler, Matthieu Wyart

Mach. Learn. Sci. Technol., 2021

2020

How isotropic kernels learn simple invariants.

Jonas Paccolat, Stefano Spigler, Matthieu Wyart

CoRR, 2020

2019

Disentangling feature and lazy learning in deep neural networks: an empirical study.

Mario Geiger, Stefano Spigler, Arthur Jacot, Matthieu Wyart

CoRR, 2019

Asymptotic learning curves of kernel methods: empirical data v.s. Teacher-Student paradigm.

Stefano Spigler, Mario Geiger, Matthieu Wyart

CoRR, 2019

Scaling description of generalization with number of parameters in deep learning.

Mario Geiger, Arthur Jacot, Stefano Spigler, Franck Gabriel, Levent Sagun, Stéphane d'Ascoli, Giulio Biroli, Clément Hongler, Matthieu Wyart

CoRR, 2019

2018

A jamming transition from under- to over-parametrization affects loss landscape and generalization.

Stefano Spigler, Mario Geiger, Stéphane d'Ascoli, Levent Sagun, Giulio Biroli, Matthieu Wyart

CoRR, 2018

The jamming transition as a paradigm to understand the loss landscape of deep neural networks.

Mario Geiger, Stefano Spigler, Stéphane d'Ascoli, Levent Sagun, Marco Baity-Jesi, Giulio Biroli, Matthieu Wyart

CoRR, 2018

Comparing Dynamics: Deep Neural Networks versus Glassy Systems.

Marco Baity-Jesi, Levent Sagun, Mario Geiger, Stefano Spigler, Gérard Ben Arous, Chiara Cammarota, Yann LeCun, Matthieu Wyart, Giulio Biroli

Proceedings of the 35th International Conference on Machine Learning, 2018