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The Hessian perspective into the Nature of Convolutional Neural Networks

The Hessian perspective into the Nature of Convolutional Neural Networks

16 May 2023
Sidak Pal Singh
Thomas Hofmann
Bernhard Schölkopf
ArXiv (abs)PDFHTML

Papers citing "The Hessian perspective into the Nature of Convolutional Neural Networks"

21 / 21 papers shown
Title
Accelerating Neural Network Training Along Sharp and Flat Directions
Accelerating Neural Network Training Along Sharp and Flat Directions
Daniyar Zakarin
Sidak Pal Singh
ODL
68
0
0
17 May 2025
Theoretical characterisation of the Gauss-Newton conditioning in Neural Networks
Theoretical characterisation of the Gauss-Newton conditioning in Neural Networks
Jim Zhao
Sidak Pal Singh
Aurelien Lucchi
AI4CE
116
0
0
04 Nov 2024
What Does It Mean to Be a Transformer? Insights from a Theoretical Hessian Analysis
What Does It Mean to Be a Transformer? Insights from a Theoretical Hessian Analysis
Weronika Ormaniec
Felix Dangel
Sidak Pal Singh
113
7
0
14 Oct 2024
Analytic Insights into Structure and Rank of Neural Network Hessian Maps
Analytic Insights into Structure and Rank of Neural Network Hessian Maps
Sidak Pal Singh
Gregor Bachmann
Thomas Hofmann
FAtt
70
37
0
30 Jun 2021
MLP-Mixer: An all-MLP Architecture for Vision
MLP-Mixer: An all-MLP Architecture for Vision
Ilya O. Tolstikhin
N. Houlsby
Alexander Kolesnikov
Lucas Beyer
Xiaohua Zhai
...
Andreas Steiner
Daniel Keysers
Jakob Uszkoreit
Mario Lucic
Alexey Dosovitskiy
423
2,682
0
04 May 2021
Dissecting Hessian: Understanding Common Structure of Hessian in Neural
  Networks
Dissecting Hessian: Understanding Common Structure of Hessian in Neural Networks
Yikai Wu
Xingyu Zhu
Chenwei Wu
Annie Wang
Rong Ge
103
45
0
08 Oct 2020
Theory of Deep Convolutional Neural Networks II: Spherical Analysis
Theory of Deep Convolutional Neural Networks II: Spherical Analysis
Zhiying Fang
Han Feng
Shuo Huang
Ding-Xuan Zhou
94
37
0
28 Jul 2020
PyHessian: Neural Networks Through the Lens of the Hessian
PyHessian: Neural Networks Through the Lens of the Hessian
Z. Yao
A. Gholami
Kurt Keutzer
Michael W. Mahoney
ODL
63
303
0
16 Dec 2019
Fantastic Generalization Measures and Where to Find Them
Fantastic Generalization Measures and Where to Find Them
Yiding Jiang
Behnam Neyshabur
H. Mobahi
Dilip Krishnan
Samy Bengio
AI4CE
139
610
0
04 Dec 2019
Information-Theoretic Local Minima Characterization and Regularization
Information-Theoretic Local Minima Characterization and Regularization
Zhiwei Jia
Hao Su
64
19
0
19 Nov 2019
Limitations of the Empirical Fisher Approximation for Natural Gradient
  Descent
Limitations of the Empirical Fisher Approximation for Natural Gradient Descent
Frederik Kunstner
Lukas Balles
Philipp Hennig
81
218
0
29 May 2019
1D Convolutional Neural Networks and Applications: A Survey
1D Convolutional Neural Networks and Applications: A Survey
S. Kiranyaz
Onur Avcı
Osama Abdeljaber
T. Ince
Moncef Gabbouj
D. Inman
3DV
85
1,930
0
09 May 2019
An Investigation into Neural Net Optimization via Hessian Eigenvalue
  Density
An Investigation into Neural Net Optimization via Hessian Eigenvalue Density
Behrooz Ghorbani
Shankar Krishnan
Ying Xiao
ODL
78
326
0
29 Jan 2019
Gradient Descent Happens in a Tiny Subspace
Gradient Descent Happens in a Tiny Subspace
Guy Gur-Ari
Daniel A. Roberts
Ethan Dyer
100
233
0
12 Dec 2018
The Singular Values of Convolutional Layers
The Singular Values of Convolutional Layers
Hanie Sedghi
Vineet Gupta
Philip M. Long
FAtt
86
203
0
26 May 2018
Overcoming catastrophic forgetting in neural networks
Overcoming catastrophic forgetting in neural networks
J. Kirkpatrick
Razvan Pascanu
Neil C. Rabinowitz
J. Veness
Guillaume Desjardins
...
A. Grabska-Barwinska
Demis Hassabis
Claudia Clopath
D. Kumaran
R. Hadsell
CLL
372
7,547
0
02 Dec 2016
Eigenvalues of the Hessian in Deep Learning: Singularity and Beyond
Eigenvalues of the Hessian in Deep Learning: Singularity and Beyond
Levent Sagun
Léon Bottou
Yann LeCun
UQCV
91
236
0
22 Nov 2016
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp
  Minima
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima
N. Keskar
Dheevatsa Mudigere
J. Nocedal
M. Smelyanskiy
P. T. P. Tang
ODL
429
2,945
0
15 Sep 2016
Optimizing Neural Networks with Kronecker-factored Approximate Curvature
Optimizing Neural Networks with Kronecker-factored Approximate Curvature
James Martens
Roger C. Grosse
ODL
104
1,023
0
19 Mar 2015
Identifying and attacking the saddle point problem in high-dimensional
  non-convex optimization
Identifying and attacking the saddle point problem in high-dimensional non-convex optimization
Yann N. Dauphin
Razvan Pascanu
Çağlar Gülçehre
Kyunghyun Cho
Surya Ganguli
Yoshua Bengio
ODL
129
1,389
0
10 Jun 2014
Invariant Scattering Convolution Networks
Invariant Scattering Convolution Networks
Joan Bruna
S. Mallat
129
1,279
0
05 Mar 2012
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