Lorenzo Giambagli

According to our database, Lorenzo Giambagli authored at least 11 papers between 2020 and 2024.

Collaborative distances:

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

2024

Stable attractors for neural networks classification via ordinary differential equations (SA-nODE).

Raffaele Marino, Lorenzo Buffoni, Lorenzo Chicchi, Lorenzo Giambagli, Duccio Fanelli

Mach. Learn. Sci. Technol., 2024

Deterministic versus stochastic dynamical classifiers: opposing random adversarial attacks with noise.

Lorenzo Chicchi, Duccio Fanelli, Diego Febbe, Lorenzo Buffoni, Francesca Di Patti, Lorenzo Giambagli, Raffaele Marino

CoRR, 2024

Learning in Wilson-Cowan model for metapopulation.

Raffaele Marino, Lorenzo Buffoni, Lorenzo Chicchi, Francesca Di Patti, Diego Febbe, Lorenzo Giambagli, Duccio Fanelli

CoRR, 2024

Automatic Input Feature Relevance via Spectral Neural Networks.

Lorenzo Chicchi, Lorenzo Buffoni, Diego Febbe, Lorenzo Giambagli, Raffaele Marino, Duccio Fanelli

CoRR, 2024

Kernel Shape Renormalization In Bayesian Shallow Networks: a Gaussian Process Perspective.

Rosalba Pacelli, Lorenzo Giambagli, Paolo Baglioni

Proceedings of the IEEE Workshop on Complexity in Engineering, 2024

2023

Complex Recurrent Spectral Network.

Lorenzo Chicchi, Lorenzo Giambagli, Lorenzo Buffoni, Raffaele Marino, Duccio Fanelli

CoRR, 2023

A Bridge between Dynamical Systems and Machine Learning: Engineered Ordinary Differential Equations as Classification Algorithm (EODECA).

Raffaele Marino, Lorenzo Giambagli, Lorenzo Chicchi, Lorenzo Buffoni, Duccio Fanelli

CoRR, 2023

How a Student becomes a Teacher: learning and forgetting through Spectral methods.

Lorenzo Giambagli, Lorenzo Buffoni, Lorenzo Chicchi, Duccio Fanelli

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Recurrent Spectral Network (RSN): shaping the basin of attraction of a discrete map to reach automated classification.

Lorenzo Chicchi, Duccio Fanelli, Lorenzo Giambagli, Lorenzo Buffoni, Timoteo Carletti

CoRR, 2022

2021

On the training of sparse and dense deep neural networks: less parameters, same performance.

Lorenzo Chicchi, Lorenzo Giambagli, Lorenzo Buffoni, Timoteo Carletti, Marco Ciavarella, Duccio Fanelli

CoRR, 2021

2020

Machine learning in spectral domain.

Lorenzo Giambagli, Lorenzo Buffoni, Timoteo Carletti, Walter Nocentini, Duccio Fanelli

CoRR, 2020