Rate of Convergence of Polynomial Networks to Gaussian Processes

4 November 2021

Papers citing "Rate of Convergence of Polynomial Networks to Gaussian Processes"

11 / 11 papers shown

Title
Finite Neural Networks as Mixtures of Gaussian Processes: From Provable Error Bounds to Prior Selection Steven Adams A. Patané Morteza Lahijanian Luca Laurenti BDL 36 2 0 26 Jul 2024
Spectral complexity of deep neural networks Simmaco Di Lillo Domenico Marinucci Michele Salvi Stefano Vigogna BDL 82 1 0 15 May 2024
Wide Deep Neural Networks with Gaussian Weights are Very Close to Gaussian Processes Dario Trevisan UQCV BDL 30 7 0 18 Dec 2023
Quantitative CLTs in Deep Neural Networks Stefano Favaro Boris Hanin Domenico Marinucci I. Nourdin G. Peccati BDL 33 12 0 12 Jul 2023
A Quantitative Functional Central Limit Theorem for Shallow Neural Networks Valentina Cammarota Domenico Marinucci M. Salvi Stefano Vigogna 42 7 0 29 Jun 2023
Gaussian random field approximation via Stein's method with applications to wide random neural networks Krishnakumar Balasubramanian L. Goldstein Nathan Ross Adil Salim 32 8 0 28 Jun 2023
Large-width asymptotics for ReLU neural networks with $α$ -Stable initializations Stefano Favaro S. Fortini Stefano Peluchetti 20 2 0 16 Jun 2022
Convergence of neural networks to Gaussian mixture distribution Yasuhiko Asao Ryotaro Sakamoto S. Takagi BDL 35 2 0 26 Apr 2022
Quantitative Gaussian Approximation of Randomly Initialized Deep Neural Networks Andrea Basteri Dario Trevisan BDL 24 21 0 14 Mar 2022
Deep Stable neural networks: large-width asymptotics and convergence rates Stefano Favaro S. Fortini Stefano Peluchetti BDL 30 14 0 02 Aug 2021
Non-asymptotic approximations of neural networks by Gaussian processes Ronen Eldan Dan Mikulincer T. Schramm 38 24 0 17 Feb 2021