Publications

The GRAFIA results are collected in the following working papers and peer-reviewed publications (members of the project in bold.)

1. V. Cammarota, D. Marinucci, M. Salvi, S. Vigogna (2023). A Quantitative Functional Central Limit Theorem for Shallow Neural Networks. Preprint arXiv:2306.16932.

2. S. Favaro, B. Hanin, D. Marinucci, I. Nourdin, G. Peccati (2023). Quantitative CLTs in Deep Neural Networks. Preprint arXiv:2307.06092.

3. L. Makowiec, M. Salvi, R. Sun (2023). Diameter of uniform spanning trees on random weighted graphs. Preprint arXiv:2311.01808.

4. D. Marinucci, M. Rossi, A.P. Todino (2023). Laguerre Expansion for Nodal Volumes and Applications. Preprint arXiv:2312.09962.

5. V. Cammarota, R.W. Maffucci, D. Marinucci, M. Rossi (2023). Correlation Structure and Resonant Pairs for Arithmetic Random Waves. Preprint arXiv:2312.13166.

6. A. Caponera, M. Rossi, M.D. Ruiz Medina (2024). Sojourn functionals of time-dependent chi-squared random fields on two point homogeneous spaces. Preprint arXiv:2403.17538.

7. S. Di Lillo, D. Marinucci, M. Salvi, S. Vigogna (2024). Spectral complexity of deep neural networks. Preprint arXiv:2405.09541.