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Towards Practical Control of Singular Values of Convolutional Layers

Towards Practical Control of Singular Values of Convolutional Layers

24 November 2022
Alexandra Senderovich
Ekaterina Bulatova
Anton Obukhov
M. Rakhuba
    AAML
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Papers citing "Towards Practical Control of Singular Values of Convolutional Layers"

32 / 32 papers shown
Title
On the Surprising Effectiveness of Spectrum Clipping in Learning Stable Linear Dynamics
On the Surprising Effectiveness of Spectrum Clipping in Learning Stable Linear Dynamics
Hanyao Guo
Yunhai Han
Harish Ravichandar
123
0
0
02 Dec 2024
TT-NF: Tensor Train Neural Fields
TT-NF: Tensor Train Neural Fields
Anton Obukhov
Mikhail (Misha) Usvyatsov
Daniel Gehrig
Konrad Schindler
Luc Van Gool
64
7
0
30 Sep 2022
Training Scale-Invariant Neural Networks on the Sphere Can Happen in
  Three Regimes
Training Scale-Invariant Neural Networks on the Sphere Can Happen in Three Regimes
M. Kodryan
E. Lobacheva
M. Nakhodnov
Dmitry Vetrov
66
17
0
08 Sep 2022
TTOpt: A Maximum Volume Quantized Tensor Train-based Optimization and
  its Application to Reinforcement Learning
TTOpt: A Maximum Volume Quantized Tensor Train-based Optimization and its Application to Reinforcement Learning
Konstantin Sozykin
Andrei Chertkov
R. Schutski
Anh-Huy Phan
A. Cichocki
Ivan Oseledets
43
35
0
30 Apr 2022
Generative Adversarial Networks
Generative Adversarial Networks
Gilad Cohen
Raja Giryes
GAN
225
30,089
0
01 Mar 2022
On the Practicality of Deterministic Epistemic Uncertainty
On the Practicality of Deterministic Epistemic Uncertainty
Janis Postels
Mattia Segu
Tao Sun
Luca Sieber
Luc Van Gool
Feng Yu
Federico Tombari
UQCV
68
60
0
01 Jul 2021
Skew Orthogonal Convolutions
Skew Orthogonal Convolutions
Sahil Singla
Soheil Feizi
63
69
0
24 May 2021
Spectral Tensor Train Parameterization of Deep Learning Layers
Spectral Tensor Train Parameterization of Deep Learning Layers
Anton Obukhov
M. Rakhuba
Alexander Liniger
Zhiwu Huang
Stamatios Georgoulis
Dengxin Dai
Luc Van Gool
53
10
0
07 Mar 2021
Reparameterizing Convolutions for Incremental Multi-Task Learning
  without Task Interference
Reparameterizing Convolutions for Incremental Multi-Task Learning without Task Interference
Menelaos Kanakis
David Brüggemann
Suman Saha
Stamatios Georgoulis
Anton Obukhov
Luc Van Gool
CLL
46
72
0
24 Jul 2020
T-Basis: a Compact Representation for Neural Networks
T-Basis: a Compact Representation for Neural Networks
Anton Obukhov
M. Rakhuba
Stamatios Georgoulis
Menelaos Kanakis
Dengxin Dai
Luc Van Gool
65
27
0
13 Jul 2020
Reliable evaluation of adversarial robustness with an ensemble of
  diverse parameter-free attacks
Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks
Francesco Croce
Matthias Hein
AAML
211
1,837
0
03 Mar 2020
PyTorch: An Imperative Style, High-Performance Deep Learning Library
PyTorch: An Imperative Style, High-Performance Deep Learning Library
Adam Paszke
Sam Gross
Francisco Massa
Adam Lerer
James Bradbury
...
Sasank Chilamkurthy
Benoit Steiner
Lu Fang
Junjie Bai
Soumith Chintala
ODL
359
42,299
0
03 Dec 2019
Preventing Gradient Attenuation in Lipschitz Constrained Convolutional
  Networks
Preventing Gradient Attenuation in Lipschitz Constrained Convolutional Networks
Qiyang Li
Saminul Haque
Cem Anil
James Lucas
Roger C. Grosse
Joern-Henrik Jacobsen
80
115
0
03 Nov 2019
Spectral Regularization for Combating Mode Collapse in GANs
Spectral Regularization for Combating Mode Collapse in GANs
Kanglin Liu
Wenming Tang
Fei Zhou
Guoping Qiu
GAN
DRL
37
82
0
29 Aug 2019
Stable Rank Normalization for Improved Generalization in Neural Networks
  and GANs
Stable Rank Normalization for Improved Generalization in Neural Networks and GANs
Amartya Sanyal
Philip Torr
P. Dokania
58
47
0
11 Jun 2019
Benchmarking Neural Network Robustness to Common Corruptions and
  Perturbations
Benchmarking Neural Network Robustness to Common Corruptions and Perturbations
Dan Hendrycks
Thomas G. Dietterich
OOD
VLM
146
3,423
0
28 Mar 2019
SNIP: Single-shot Network Pruning based on Connection Sensitivity
SNIP: Single-shot Network Pruning based on Connection Sensitivity
Namhoon Lee
Thalaiyasingam Ajanthan
Philip Torr
VLM
229
1,196
0
04 Oct 2018
The Singular Values of Convolutional Layers
The Singular Values of Convolutional Layers
Hanie Sedghi
Vineet Gupta
Philip M. Long
FAtt
81
202
0
26 May 2018
Regularisation of Neural Networks by Enforcing Lipschitz Continuity
Regularisation of Neural Networks by Enforcing Lipschitz Continuity
Henry Gouk
E. Frank
Bernhard Pfahringer
M. Cree
145
475
0
12 Apr 2018
The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks
The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks
Jonathan Frankle
Michael Carbin
202
3,457
0
09 Mar 2018
Wide Compression: Tensor Ring Nets
Wide Compression: Tensor Ring Nets
Wenqi Wang
Yifan Sun
Brian Eriksson
Wenlin Wang
Vaneet Aggarwal
54
169
0
25 Feb 2018
Spectrally-normalized margin bounds for neural networks
Spectrally-normalized margin bounds for neural networks
Peter L. Bartlett
Dylan J. Foster
Matus Telgarsky
ODL
179
1,216
0
26 Jun 2017
On Calibration of Modern Neural Networks
On Calibration of Modern Neural Networks
Chuan Guo
Geoff Pleiss
Yu Sun
Kilian Q. Weinberger
UQCV
241
5,812
0
14 Jun 2017
Spectral Norm Regularization for Improving the Generalizability of Deep
  Learning
Spectral Norm Regularization for Improving the Generalizability of Deep Learning
Yuichi Yoshida
Takeru Miyato
77
332
0
31 May 2017
Parseval Networks: Improving Robustness to Adversarial Examples
Parseval Networks: Improving Robustness to Adversarial Examples
Moustapha Cissé
Piotr Bojanowski
Edouard Grave
Yann N. Dauphin
Nicolas Usunier
AAML
136
806
0
28 Apr 2017
Ultimate tensorization: compressing convolutional and FC layers alike
Ultimate tensorization: compressing convolutional and FC layers alike
T. Garipov
D. Podoprikhin
Alexander Novikov
Dmitry Vetrov
61
190
0
10 Nov 2016
Wide Residual Networks
Wide Residual Networks
Sergey Zagoruyko
N. Komodakis
310
7,971
0
23 May 2016
Structured Pruning of Deep Convolutional Neural Networks
Structured Pruning of Deep Convolutional Neural Networks
S. Anwar
Kyuyeon Hwang
Wonyong Sung
87
747
0
29 Dec 2015
Compression of Deep Convolutional Neural Networks for Fast and Low Power
  Mobile Applications
Compression of Deep Convolutional Neural Networks for Fast and Low Power Mobile Applications
Yong-Deok Kim
Eunhyeok Park
S. Yoo
Taelim Choi
Lu Yang
Dongjun Shin
102
893
0
20 Nov 2015
Tensorizing Neural Networks
Tensorizing Neural Networks
Alexander Novikov
D. Podoprikhin
A. Osokin
Dmitry Vetrov
89
881
0
22 Sep 2015
Explaining and Harnessing Adversarial Examples
Explaining and Harnessing Adversarial Examples
Ian Goodfellow
Jonathon Shlens
Christian Szegedy
AAML
GAN
231
19,017
0
20 Dec 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition
Very Deep Convolutional Networks for Large-Scale Image Recognition
Karen Simonyan
Andrew Zisserman
FAtt
MDE
1.3K
100,213
0
04 Sep 2014
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