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Reverse Engineering the Neural Tangent Kernel

Reverse Engineering the Neural Tangent Kernel

6 June 2021
James B. Simon
Sajant Anand
M. DeWeese
ArXivPDFHTML

Papers citing "Reverse Engineering the Neural Tangent Kernel"

7 / 7 papers shown
Title
Issues with Neural Tangent Kernel Approach to Neural Networks
Issues with Neural Tangent Kernel Approach to Neural Networks
Haoran Liu
Anthony S. Tai
David J. Crandall
Chunfeng Huang
42
0
0
19 Jan 2025
Neural Redshift: Random Networks are not Random Functions
Neural Redshift: Random Networks are not Random Functions
Damien Teney
A. Nicolicioiu
Valentin Hartmann
Ehsan Abbasnejad
103
18
0
04 Mar 2024
Mind the spikes: Benign overfitting of kernels and neural networks in
  fixed dimension
Mind the spikes: Benign overfitting of kernels and neural networks in fixed dimension
Moritz Haas
David Holzmüller
U. V. Luxburg
Ingo Steinwart
MLT
35
14
0
23 May 2023
Characterizing the Spectrum of the NTK via a Power Series Expansion
Characterizing the Spectrum of the NTK via a Power Series Expansion
Michael Murray
Hui Jin
Benjamin Bowman
Guido Montúfar
38
11
0
15 Nov 2022
Benign, Tempered, or Catastrophic: A Taxonomy of Overfitting
Benign, Tempered, or Catastrophic: A Taxonomy of Overfitting
Neil Rohit Mallinar
James B. Simon
Amirhesam Abedsoltan
Parthe Pandit
M. Belkin
Preetum Nakkiran
26
37
0
14 Jul 2022
Spectrum Dependent Learning Curves in Kernel Regression and Wide Neural
  Networks
Spectrum Dependent Learning Curves in Kernel Regression and Wide Neural Networks
Blake Bordelon
Abdulkadir Canatar
Cengiz Pehlevan
146
201
0
07 Feb 2020
Benefits of depth in neural networks
Benefits of depth in neural networks
Matus Telgarsky
151
602
0
14 Feb 2016
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