Quantitative CLTs in Deep Neural Networks

Quantitative CLTs in Deep Neural Networks

12 July 2023

Domenico Marinucci

Papers citing "Quantitative CLTs in Deep Neural Networks"

11 / 11 papers shown

Title
Fractal and Regular Geometry of Deep Neural Networks Simmaco Di Lillo Domenico Marinucci Michele Salvi S. Vigogna MDE AI4CE 29 0 0 08 Apr 2025
Student-t processes as infinite-width limits of posterior Bayesian neural networks Francesco Caporali Stefano Favaro Dario Trevisan BDL 111 0 0 06 Feb 2025
Effective Non-Random Extreme Learning Machine Daniela De Canditiis Fabiano Veglianti 64 0 0 25 Nov 2024
Proportional infinite-width infinite-depth limit for deep linear neural networks Federico Bassetti Lucia Ladelli P. Rotondo 62 0 0 22 Nov 2024
Finite Neural Networks as Mixtures of Gaussian Processes: From Provable Error Bounds to Prior Selection Steven Adams A. Patané Morteza Lahijanian Luca Laurenti BDL 23 1 0 26 Jul 2024
Wide stable neural networks: Sample regularity, functional convergence and Bayesian inverse problems Tomás Soto 22 0 0 04 Jul 2024
Breuer-Major Theorems for Hilbert Space-Valued Random Variables M. Duker Pavlos Zoubouloglou 20 0 0 19 May 2024
Wide Deep Neural Networks with Gaussian Weights are Very Close to Gaussian Processes Dario Trevisan UQCV BDL 14 6 0 18 Dec 2023
Local Kernel Renormalization as a mechanism for feature learning in overparametrized Convolutional Neural Networks R. Aiudi R. Pacelli A. Vezzani R. Burioni P. Rotondo MLT 16 10 0 21 Jul 2023
Gaussian random field approximation via Stein's method with applications to wide random neural networks Krishnakumar Balasubramanian L. Goldstein Nathan Ross Adil Salim 12 8 0 28 Jun 2023
Non-asymptotic approximations of neural networks by Gaussian processes Ronen Eldan Dan Mikulincer T. Schramm 25 24 0 17 Feb 2021