Enrico M. Malatesta

According to our database, Enrico M. Malatesta authored at least 10 papers between 2019 and 2024.

Collaborative distances:

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

2024

The twin peaks of learning neural networks.

Elizaveta Demyanenko, Christoph Feinauer, Enrico M. Malatesta, Luca Saglietti

CoRR, 2024

2023

High-dimensional manifold of solutions in neural networks: insights from statistical physics.

Enrico M. Malatesta

CoRR, 2023

The star-shaped space of solutions of the spherical negative perceptron.

Brandon Livio Annesi, Clarissa Lauditi, Carlo Lucibello, Enrico M. Malatesta, Gabriele Perugini, Fabrizio Pittorino, Luca Saglietti

CoRR, 2023

Typical and atypical solutions in non-convex neural networks with discrete and continuous weights.

Carlo Baldassi, Enrico M. Malatesta, Gabriele Perugini, Riccardo Zecchina

CoRR, 2023

The Hidden-Manifold Hopfield Model and a learning phase transition.

Matteo Negri, Clarissa Lauditi, Gabriele Perugini, Carlo Lucibello, Enrico M. Malatesta

CoRR, 2023

2021

Learning through atypical "phase transitions" in overparameterized neural networks.

Carlo Baldassi, Clarissa Lauditi, Enrico M. Malatesta, Rosalba Pacelli, Gabriele Perugini, Riccardo Zecchina

CoRR, 2021

Unveiling the structure of wide flat minima in neural networks.

Carlo Baldassi, Clarissa Lauditi, Enrico M. Malatesta, Gabriele Perugini, Riccardo Zecchina

CoRR, 2021

2020

Wide flat minima and optimal generalization in classifying high-dimensional Gaussian mixtures.

Carlo Baldassi, Enrico M. Malatesta, Matteo Negri, Riccardo Zecchina

CoRR, 2020

Entropic gradient descent algorithms and wide flat minima.

Fabrizio Pittorino, Carlo Lucibello, Christoph Feinauer, Enrico M. Malatesta, Gabriele Perugini, Carlo Baldassi, Matteo Negri, Elizaveta Demyanenko, Riccardo Zecchina

CoRR, 2020

2019

On the geometry of solutions and on the capacity of multi-layer neural networks with ReLU activations.

Carlo Baldassi, Enrico M. Malatesta, Riccardo Zecchina

CoRR, 2019