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Random ReLU Neural Networks as Non-Gaussian Processes

Random ReLU Neural Networks as Non-Gaussian Processes

Rahul Parhi
Pakshal Bohra
Ayoub El Biari
Mehrsa Pourya
Michael Unser
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Papers citing "Random ReLU Neural Networks as Non-Gaussian Processes"

16 / 16 papers shown
Title
Online Federation For Mixtures of Proprietary Agents with Black-Box Encoders
Online Federation For Mixtures of Proprietary Agents with Black-Box Encoders
Xuwei Yang
Fatemeh Tavakoli
D. B. Emerson
Anastasis Kratsios
FedML
106
0
0
30 Apr 2025
Function-Space Optimality of Neural Architectures with Multivariate Nonlinearities
Function-Space Optimality of Neural Architectures with Multivariate Nonlinearities
Rahul Parhi
Michael Unser
82
5
0
05 Oct 2023
Variation Spaces for Multi-Output Neural Networks: Insights on Multi-Task Learning and Network Compression
Variation Spaces for Multi-Output Neural Networks: Insights on Multi-Task Learning and Network Compression
Joseph Shenouda
Rahul Parhi
Kangwook Lee
Robert D. Nowak
70
13
0
25 May 2023
Deep Learning Meets Sparse Regularization: A Signal Processing Perspective
Deep Learning Meets Sparse Regularization: A Signal Processing Perspective
Rahul Parhi
Robert D. Nowak
68
25
0
23 Jan 2023
Understanding neural networks with reproducing kernel Banach spaces
Understanding neural networks with reproducing kernel Banach spaces
Francesca Bartolucci
Ernesto De Vito
Lorenzo Rosasco
Stefano Vigogna
72
50
0
20 Sep 2021
Near-Minimax Optimal Estimation With Shallow ReLU Neural Networks
Near-Minimax Optimal Estimation With Shallow ReLU Neural Networks
Rahul Parhi
Robert D. Nowak
79
38
0
18 Sep 2021
Random Neural Networks in the Infinite Width Limit as Gaussian Processes
Random Neural Networks in the Infinite Width Limit as Gaussian Processes
Boris Hanin
BDL
62
46
0
04 Jul 2021
What Kinds of Functions do Deep Neural Networks Learn? Insights from Variational Spline Theory
What Kinds of Functions do Deep Neural Networks Learn? Insights from Variational Spline Theory
Rahul Parhi
Robert D. Nowak
MLT
66
71
0
07 May 2021
Tensor Programs I: Wide Feedforward or Recurrent Neural Networks of Any Architecture are Gaussian Processes
Tensor Programs I: Wide Feedforward or Recurrent Neural Networks of Any Architecture are Gaussian Processes
Greg Yang
113
199
0
28 Oct 2019
A Function Space View of Bounded Norm Infinite Width ReLU Nets: The Multivariate Case
A Function Space View of Bounded Norm Infinite Width ReLU Nets: The Multivariate Case
Greg Ongie
Rebecca Willett
Daniel Soudry
Nathan Srebro
90
161
0
03 Oct 2019
Non-Gaussian processes and neural networks at finite widths
Non-Gaussian processes and neural networks at finite widths
Sho Yaida
79
87
0
30 Sep 2019
Asymptotics of Wide Networks from Feynman Diagrams
Asymptotics of Wide Networks from Feynman Diagrams
Ethan Dyer
Guy Gur-Ari
71
114
0
25 Sep 2019
Bayesian Deep Convolutional Networks with Many Channels are Gaussian Processes
Bayesian Deep Convolutional Networks with Many Channels are Gaussian Processes
Roman Novak
Lechao Xiao
Jaehoon Lee
Yasaman Bahri
Greg Yang
Jiri Hron
Daniel A. Abolafia
Jeffrey Pennington
Jascha Narain Sohl-Dickstein
UQCV
BDL
63
309
0
11 Oct 2018
Deep Convolutional Networks as shallow Gaussian Processes
Deep Convolutional Networks as shallow Gaussian Processes
Adrià Garriga-Alonso
C. Rasmussen
Laurence Aitchison
BDL
UQCV
106
271
0
16 Aug 2018
Gaussian Process Behaviour in Wide Deep Neural Networks
Gaussian Process Behaviour in Wide Deep Neural Networks
A. G. Matthews
Mark Rowland
Jiri Hron
Richard Turner
Zoubin Ghahramani
BDL
144
559
0
30 Apr 2018
Deep Neural Networks as Gaussian Processes
Deep Neural Networks as Gaussian Processes
Jaehoon Lee
Yasaman Bahri
Roman Novak
S. Schoenholz
Jeffrey Pennington
Jascha Narain Sohl-Dickstein
UQCV
BDL
125
1,093
0
01 Nov 2017

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