Local kernel renormalization as a mechanism for feature learning in overparametrized convolutional neural networks R Aiudi, R Pacelli, P Baglioni, A Vezzani, R Burioni, P Rotondo
Nature Communications 16 (1), 568, 2025
14 2025 Predictive power of a bayesian effective action for fully connected one hidden layer neural networks in the proportional limit P Baglioni, R Pacelli, R Aiudi, F Di Renzo, A Vezzani, R Burioni, ...
Physical Review Letters 133 (2), 027301, 2024
8 2024 Numerical Stochastic Perturbation Theory around instantons P Baglioni, F Di Renzo
The 39th International Symposium on Lattice Field Theory (LATTICE2022) 430 (362), 2023
3 2023 Large fluctuations in NSPT computations: a lesson from P Baglioni, F Di Renzo
arXiv preprint arXiv:2402.01322, 2024
2 2024 NSPT for P Baglioni, F Di Renzo
The 40th International Symposium on Lattice Field Theory (LATTICE2023) 453 (366), 2024
1 2024 Kernel shape renormalization explains output-output correlations in finite Bayesian one-hidden-layer networks P Baglioni, L Giambagli, A Vezzani, R Burioni, P Rotondo, R Pacelli
arXiv preprint arXiv:2412.15911, 2024
2024 Taming NSPT fluctuations in P Baglioni, F Di Renzo
European network for Particle physics, Lattice field theory and Extreme …, 2024
2024 Kernel Shape Renormalization In Bayesian Shallow Networks: a Gaussian Process Perspective R Pacelli, L Giambagli, P Baglioni
2024 IEEE Workshop on Complexity in Engineering (COMPENG), 1-6, 2024
2024 Confronting Large Fluctuations in Numerical Stochastic Perturbation Theory P Baglioni
Università degli Studi di Parma. Dipartimento di Scienze Matematiche …, 2024
2024 
Rosalba PacelliINFN PadovaEmail verificata su pd.infn.it