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Gaussian random field approximation via Stein's method with applications to wide random neural networks
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Gaussian random field approximation via Stein's method with applications to wide random neural networks

Krishnakumar Balasubramanian
L. Goldstein
Nathan Ross
Adil Salim
ArXiv (abs)PDFHTML

Papers citing "Gaussian random field approximation via Stein's method with applications to wide random neural networks"

7 / 7 papers shown
Title
Critical Points of Random Neural Networks
Critical Points of Random Neural Networks
Simmaco Di Lillo
53
0
0
22 May 2025
Finite Neural Networks as Mixtures of Gaussian Processes: From Provable Error Bounds to Prior Selection
Finite Neural Networks as Mixtures of Gaussian Processes: From Provable Error Bounds to Prior Selection
Steven Adams
A. Patané
Morteza Lahijanian
Luca Laurenti
BDL
81
3
0
26 Jul 2024
Spectral complexity of deep neural networks
Spectral complexity of deep neural networks
Simmaco Di Lillo
Domenico Marinucci
Michele Salvi
Stefano Vigogna
BDL
175
2
0
15 May 2024
Wide Deep Neural Networks with Gaussian Weights are Very Close to Gaussian Processes
Wide Deep Neural Networks with Gaussian Weights are Very Close to Gaussian Processes
Dario Trevisan
UQCVBDL
88
7
0
18 Dec 2023
Quantitative CLTs in Deep Neural Networks
Quantitative CLTs in Deep Neural Networks
Stefano Favaro
Boris Hanin
Domenico Marinucci
I. Nourdin
G. Peccati
BDL
138
16
0
12 Jul 2023
Gaussian Pre-Activations in Neural Networks: Myth or Reality?
Gaussian Pre-Activations in Neural Networks: Myth or Reality?
Pierre Wolinski
Julyan Arbel
AI4CE
215
9
0
24 May 2022
Stein's method, smoothing and functional approximation
Stein's method, smoothing and functional approximation
A. Barbour
Nathan Ross
Guangqu Zheng
85
5
0
03 Jun 2021

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