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Orthogonal Convolutional Neural Networks

Orthogonal Convolutional Neural Networks

27 November 2019
Jiayun Wang
Yubei Chen
Rudrasis Chakraborty
Stella X. Yu
ArXivPDFHTML

Papers citing "Orthogonal Convolutional Neural Networks"

35 / 35 papers shown
Title
Cross-Branch Orthogonality for Improved Generalization in Face Deepfake Detection
Cross-Branch Orthogonality for Improved Generalization in Face Deepfake Detection
Tharindu Fernando
Clinton Fookes
S. Sridharan
Simon Denman
41
0
0
08 May 2025
Bayesian Quantum Orthogonal Neural Networks for Anomaly Detection
Bayesian Quantum Orthogonal Neural Networks for Anomaly Detection
Natansh Mathur
Brian Coyle
Nishant Jain
Snehal Raj
Akshat Tandon
Jasper Simon Krauser
Rainer Stoessel
25
0
0
25 Apr 2025
SPLITZ: Certifiable Robustness via Split Lipschitz Randomized Smoothing
SPLITZ: Certifiable Robustness via Split Lipschitz Randomized Smoothing
Meiyu Zhong
Ravi Tandon
36
3
0
03 Jul 2024
Restyling Unsupervised Concept Based Interpretable Networks with Generative Models
Restyling Unsupervised Concept Based Interpretable Networks with Generative Models
Jayneel Parekh
Quentin Bouniot
Pavlo Mozharovskyi
A. Newson
Florence dÁlché-Buc
SSL
61
1
0
01 Jul 2024
Get the Best of Both Worlds: Improving Accuracy and Transferability by
  Grassmann Class Representation
Get the Best of Both Worlds: Improving Accuracy and Transferability by Grassmann Class Representation
Haoqi Wang
Zhizhong Li
Wayne Zhang
15
2
0
03 Aug 2023
Group Orthogonalization Regularization For Vision Models Adaptation and
  Robustness
Group Orthogonalization Regularization For Vision Models Adaptation and Robustness
Yoav Kurtz
Noga Bar
Raja Giryes
24
0
0
16 Jun 2023
Generalizing and Decoupling Neural Collapse via Hyperspherical
  Uniformity Gap
Generalizing and Decoupling Neural Collapse via Hyperspherical Uniformity Gap
Weiyang Liu
L. Yu
Adrian Weller
Bernhard Schölkopf
32
17
0
11 Mar 2023
TinyAD: Memory-efficient anomaly detection for time series data in
  Industrial IoT
TinyAD: Memory-efficient anomaly detection for time series data in Industrial IoT
Yuting Sun
Tong Chen
Quoc Viet Hung Nguyen
Hongzhi Yin
21
12
0
07 Mar 2023
Koopman-based generalization bound: New aspect for full-rank weights
Koopman-based generalization bound: New aspect for full-rank weights
Yuka Hashimoto
Sho Sonoda
Isao Ishikawa
Atsushi Nitanda
Taiji Suzuki
11
2
0
12 Feb 2023
Deep Diversity-Enhanced Feature Representation of Hyperspectral Images
Deep Diversity-Enhanced Feature Representation of Hyperspectral Images
Jinhui Hou
Zhiyu Zhu
Junhui Hou
Hui Liu
Huanqiang Zeng
Deyu Meng
18
6
0
15 Jan 2023
Learnable Heterogeneous Convolution: Learning both topology and strength
Learnable Heterogeneous Convolution: Learning both topology and strength
Rongzhen Zhao
Zhenzhi Wu
Qikun Zhang
24
6
0
13 Jan 2023
Orthogonal SVD Covariance Conditioning and Latent Disentanglement
Orthogonal SVD Covariance Conditioning and Latent Disentanglement
Yue Song
N. Sebe
Wei Wang
26
6
0
11 Dec 2022
Dynamical systems' based neural networks
Dynamical systems' based neural networks
E. Celledoni
Davide Murari
B. Owren
Carola-Bibiane Schönlieb
Ferdia Sherry
OOD
40
10
0
05 Oct 2022
Efficient CNN with uncorrelated Bag of Features pooling
Efficient CNN with uncorrelated Bag of Features pooling
Firas Laakom
Jenni Raitoharju
Alexandros Iosifidis
M. Gabbouj
32
2
0
22 Sep 2022
HAGCN : Network Decentralization Attention Based Heterogeneity-Aware
  Spatiotemporal Graph Convolution Network for Traffic Signal Forecasting
HAGCN : Network Decentralization Attention Based Heterogeneity-Aware Spatiotemporal Graph Convolution Network for Traffic Signal Forecasting
Junkyu Jang
Sunghyuk Park
32
1
0
05 Sep 2022
Almost-Orthogonal Layers for Efficient General-Purpose Lipschitz
  Networks
Almost-Orthogonal Layers for Efficient General-Purpose Lipschitz Networks
Bernd Prach
Christoph H. Lampert
32
35
0
05 Aug 2022
Improving Covariance Conditioning of the SVD Meta-layer by Orthogonality
Improving Covariance Conditioning of the SVD Meta-layer by Orthogonality
Yue Song
N. Sebe
Wei Wang
16
8
0
05 Jul 2022
Maximum Class Separation as Inductive Bias in One Matrix
Maximum Class Separation as Inductive Bias in One Matrix
Tejaswi Kasarla
Gertjan J. Burghouts
Max van Spengler
Elise van der Pol
Rita Cucchiara
Pascal Mettes
26
22
0
17 Jun 2022
Entangled Residual Mappings
Entangled Residual Mappings
Mathias Lechner
Ramin Hasani
Z. Babaiee
Radu Grosu
Daniela Rus
T. Henzinger
Sepp Hochreiter
6
4
0
02 Jun 2022
Feedback Gradient Descent: Efficient and Stable Optimization with
  Orthogonality for DNNs
Feedback Gradient Descent: Efficient and Stable Optimization with Orthogonality for DNNs
Fanchen Bu
D. Chang
17
6
0
12 May 2022
Riemannian Hamiltonian methods for min-max optimization on manifolds
Riemannian Hamiltonian methods for min-max optimization on manifolds
Andi Han
Bamdev Mishra
Pratik Jawanpuria
Pawan Kumar
Junbin Gao
30
16
0
25 Apr 2022
projUNN: efficient method for training deep networks with unitary
  matrices
projUNN: efficient method for training deep networks with unitary matrices
B. Kiani
Randall Balestriero
Yann LeCun
S. Lloyd
36
32
0
10 Mar 2022
SeamlessGAN: Self-Supervised Synthesis of Tileable Texture Maps
SeamlessGAN: Self-Supervised Synthesis of Tileable Texture Maps
Carlos Rodriguez-Pardo
Elena Garces
GAN
12
24
0
13 Jan 2022
Systematic Literature Review: Quantum Machine Learning and its
  applications
Systematic Literature Review: Quantum Machine Learning and its applications
David Peral García
Juan Cruz-Benito
Francisco José García-Penalvo
30
119
0
11 Jan 2022
Channel redundancy and overlap in convolutional neural networks with
  channel-wise NNK graphs
Channel redundancy and overlap in convolutional neural networks with channel-wise NNK graphs
David Bonet
Antonio Ortega
Javier Ruiz-Hidalgo
Sarath Shekkizhar
GNN
31
7
0
18 Oct 2021
Weight Evolution: Improving Deep Neural Networks Training through
  Evolving Inferior Weight Values
Weight Evolution: Improving Deep Neural Networks Training through Evolving Inferior Weight Values
Zhenquan Lin
K. Guo
Xiaofen Xing
Xiangmin Xu
ODL
24
1
0
09 Oct 2021
Orthogonal Graph Neural Networks
Orthogonal Graph Neural Networks
Kai Guo
Kaixiong Zhou
Xia Hu
Yu Li
Yi Chang
Xin Wang
43
34
0
23 Sep 2021
Orthogonal Jacobian Regularization for Unsupervised Disentanglement in
  Image Generation
Orthogonal Jacobian Regularization for Unsupervised Disentanglement in Image Generation
Yuxiang Wei
Yupeng Shi
Xiao-Chang Liu
Zhilong Ji
Yuan Gao
Zhongqin Wu
W. Zuo
21
55
0
17 Aug 2021
Existence, Stability and Scalability of Orthogonal Convolutional Neural
  Networks
Existence, Stability and Scalability of Orthogonal Convolutional Neural Networks
E. M. Achour
Franccois Malgouyres
Franck Mamalet
16
20
0
12 Aug 2021
Orthogonal Ensemble Networks for Biomedical Image Segmentation
Orthogonal Ensemble Networks for Biomedical Image Segmentation
Agostina J. Larrazabal
Cesar E. Martínez
Jose Dolz
Enzo Ferrante
UQCV
16
22
0
22 May 2021
Fast Jacobian-Vector Product for Deep Networks
Fast Jacobian-Vector Product for Deep Networks
Randall Balestriero
Richard Baraniuk
23
4
0
01 Apr 2021
Improving Unsupervised Domain Adaptation by Reducing Bi-level Feature
  Redundancy
Improving Unsupervised Domain Adaptation by Reducing Bi-level Feature Redundancy
Mengzhu Wang
Xiang Zhang
L. Lan
Wei Wang
Huibin Tan
Zhigang Luo
AI4CE
37
1
0
28 Dec 2020
Physics-Informed Neural State Space Models via Learning and Evolution
Physics-Informed Neural State Space Models via Learning and Evolution
Elliott Skomski
Ján Drgoňa
Aaron Tuor
PINN
AI4CE
19
9
0
26 Nov 2020
Deep Isometric Learning for Visual Recognition
Deep Isometric Learning for Visual Recognition
Haozhi Qi
Chong You
X. Wang
Yi-An Ma
Jitendra Malik
VLM
24
53
0
30 Jun 2020
Optimization on Submanifolds of Convolution Kernels in CNNs
Optimization on Submanifolds of Convolution Kernels in CNNs
Mete Ozay
Takayuki Okatani
43
46
0
22 Oct 2016
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