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Modern Stochastics: Theory and Applications


Cited by 4
A quantitative functional central limit theorem for shallow neural networks

A caveat on metrizing convergence in distribution on Hilbert spaces
Federico Bassetti, Solesne Bourguin, Simon Campese, Giovanni Peccati
https://doi.org/10.1016/j.spl.2026.110671
Journal  Statistics & Probability Letters Volume 233 (2026), p. 110671
Large and moderate deviations for Gaussian neural networks
Claudio Macci, Barbara Pacchiarotti, Giovanni Luca Torrisi
https://doi.org/10.1017/jpr.2025.10024
Journal  Journal of Applied Probability (2025), p. 1
Quantitative CLTs in deep neural networks
S. Favaro, B. Hanin, D. Marinucci, I. Nourdin, G. Peccati
https://doi.org/10.1007/s00440-025-01360-1
Journal  Probability Theory and Related Fields Volume 191, Issue 3-4 (2025), p. 933
Spectral Complexity of Deep Neural Networks
Simmaco Di Lillo, Domenico Marinucci, Michele Salvi, Stefano Vigogna
https://doi.org/10.1137/24M1675746
Journal  SIAM Journal on Mathematics of Data Science Volume 7, Issue 3 (2025), p. 1154


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