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Harmonic Networks: Deep Translation and Rotation Equivariance
v1v2 (latest)

Harmonic Networks: Deep Translation and Rotation Equivariance

14 December 2016
Daniel E. Worrall
Stephan J. Garbin
Daniyar Turmukhambetov
Gabriel J. Brostow
ArXiv (abs)PDFHTML

Papers citing "Harmonic Networks: Deep Translation and Rotation Equivariance"

50 / 419 papers shown
Title
Circular-Symmetric Correlation Layer based on FFT
Circular-Symmetric Correlation Layer based on FFT
Bahar Azari
Deniz Erdogmus
45
1
0
26 Jul 2021
6DCNN with roto-translational convolution filters for volumetric data
  processing
6DCNN with roto-translational convolution filters for volumetric data processing
Dmitrii Zhemchuzhnikov
Ilia Igashov
Sergei Grudinin
3DPC
73
2
0
26 Jul 2021
Invariance-based Multi-Clustering of Latent Space Embeddings for
  Equivariant Learning
Invariance-based Multi-Clustering of Latent Space Embeddings for Equivariant Learning
Minh Nguyen
A. Roy
Haoran Zhang
BDLDRL
97
1
0
25 Jul 2021
Geometric Data Augmentation Based on Feature Map Ensemble
Geometric Data Augmentation Based on Feature Map Ensemble
Takashi Shibata
Masayuki Tanaka
Masatoshi Okutomi
67
0
0
22 Jul 2021
Parametric Scattering Networks
Parametric Scattering Networks
Shanel Gauthier
Benjamin Thérien
Laurent Alsene-Racicot
Muawiz Chaudhary
Irina Rish
Eugene Belilovsky
Michael Eickenberg
Guy Wolf
88
18
0
20 Jul 2021
PICASO: Permutation-Invariant Cascaded Attentional Set Operator
PICASO: Permutation-Invariant Cascaded Attentional Set Operator
Samira Zare
H. Nguyen
101
5
0
17 Jul 2021
Universal approximation and model compression for radial neural networks
Universal approximation and model compression for radial neural networks
I. Ganev
Twan van Laarhoven
Robin Walters
94
10
0
06 Jul 2021
Physics-Guided Deep Learning for Dynamical Systems: A Survey
Physics-Guided Deep Learning for Dynamical Systems: A Survey
Rui Wang
Rose Yu
AI4CEPINN
115
69
0
02 Jul 2021
Improving Sound Event Classification by Increasing Shift Invariance in
  Convolutional Neural Networks
Improving Sound Event Classification by Increasing Shift Invariance in Convolutional Neural Networks
Eduardo Fonseca
Andrés Ferraro
Xavier Serra
AI4TS
131
9
0
01 Jul 2021
Alias-Free Generative Adversarial Networks
Alias-Free Generative Adversarial Networks
Tero Karras
M. Aittala
S. Laine
Erik Härkönen
Janne Hellsten
J. Lehtinen
Timo Aila
GAN
283
1,606
0
23 Jun 2021
Training or Architecture? How to Incorporate Invariance in Neural
  Networks
Training or Architecture? How to Incorporate Invariance in Neural Networks
Kanchana Vaishnavi Gandikota
Jonas Geiping
Zorah Lähner
Adam Czapliñski
Michael Moeller
3DPCOOD
61
10
0
18 Jun 2021
Equivariance-bridged SO(2)-Invariant Representation Learning using Graph
  Convolutional Network
Equivariance-bridged SO(2)-Invariant Representation Learning using Graph Convolutional Network
Sungwon Hwang
Hyungtae Lim
Hyun Myung
47
2
0
18 Jun 2021
Equivariant Networks for Pixelized Spheres
Equivariant Networks for Pixelized Spheres
Mehran Shakerinava
Siamak Ravanbakhsh
3DPC
91
19
0
12 Jun 2021
Scale-invariant scale-channel networks: Deep networks that generalise to
  previously unseen scales
Scale-invariant scale-channel networks: Deep networks that generalise to previously unseen scales
Ylva Jansson
T. Lindeberg
91
24
0
11 Jun 2021
Group Equivariant Subsampling
Group Equivariant Subsampling
Jin Xu
Hyunjik Kim
Tom Rainforth
Yee Whye Teh
67
22
0
10 Jun 2021
Exploiting Learned Symmetries in Group Equivariant Convolutions
Exploiting Learned Symmetries in Group Equivariant Convolutions
A. Lengyel
Jan van Gemert
76
5
0
09 Jun 2021
Rotating spiders and reflecting dogs: a class conditional approach to
  learning data augmentation distributions
Rotating spiders and reflecting dogs: a class conditional approach to learning data augmentation distributions
Scott Mahan
Henry Kvinge
T. Doster
OOD
20
3
0
07 Jun 2021
Resolution learning in deep convolutional networks using scale-space
  theory
Resolution learning in deep convolutional networks using scale-space theory
Silvia L.Pintea
Nergis Tomen
Stanley F. Goes
Marco Loog
Jan van Gemert
SupRSSL
113
37
0
07 Jun 2021
Commutative Lie Group VAE for Disentanglement Learning
Commutative Lie Group VAE for Disentanglement Learning
Xinqi Zhu
Chang Xu
Dacheng Tao
CoGeDRL
85
25
0
07 Jun 2021
VolterraNet: A higher order convolutional network with group
  equivariance for homogeneous manifolds
VolterraNet: A higher order convolutional network with group equivariance for homogeneous manifolds
Monami Banerjee
Rudrasis Chakraborty
Jose J. Bouza
B. Vemuri
52
11
0
05 Jun 2021
DISCO: accurate Discrete Scale Convolutions
DISCO: accurate Discrete Scale Convolutions
Ivan Sosnovik
A. Moskalev
A. Smeulders
79
32
0
04 Jun 2021
SE(3)-equivariant prediction of molecular wavefunctions and electronic
  densities
SE(3)-equivariant prediction of molecular wavefunctions and electronic densities
Oliver T. Unke
Mihail Bogojeski
M. Gastegger
Mario Geiger
Tess E. Smidt
Klaus-Robert Muller
86
94
0
04 Jun 2021
Mesh-based graph convolutional neural networks for modeling materials
  with microstructure
Mesh-based graph convolutional neural networks for modeling materials with microstructure
A. Frankel
Cosmin Safta
Coleman Alleman
Reese E. Jones
74
15
0
04 Jun 2021
Symmetry-via-Duality: Invariant Neural Network Densities from
  Parameter-Space Correlators
Symmetry-via-Duality: Invariant Neural Network Densities from Parameter-Space Correlators
Anindita Maiti
Keegan Stoner
James Halverson
75
20
0
01 Jun 2021
Geometric Deep Learning and Equivariant Neural Networks
Geometric Deep Learning and Equivariant Neural Networks
Jan E. Gerken
J. Aronsson
Oscar Carlsson
Hampus Linander
F. Ohlsson
Christoffer Petersson
Daniel Persson
MLT
139
72
0
28 May 2021
Feature Space Targeted Attacks by Statistic Alignment
Feature Space Targeted Attacks by Statistic Alignment
Lianli Gao
Yaya Cheng
Qilong Zhang
Xing Xu
Jingkuan Song
AAML
77
33
0
25 May 2021
FILTRA: Rethinking Steerable CNN by Filter Transform
FILTRA: Rethinking Steerable CNN by Filter Transform
Yue Liu
Qili Wang
G. Lee
46
4
0
25 May 2021
Rotation invariant CNN using scattering transform for image
  classification
Rotation invariant CNN using scattering transform for image classification
Rosemberg Rodriguez
Eva Dokládalová
P. Dokládal
57
17
0
21 May 2021
Deep Permutation Equivariant Structure from Motion
Deep Permutation Equivariant Structure from Motion
Dror Moran
Hodaya Koslowsky
Yoni Kasten
Haggai Maron
Meirav Galun
Ronen Basri
3DPC
75
18
0
14 Apr 2021
Autoequivariant Network Search via Group Decomposition
Autoequivariant Network Search via Group Decomposition
Sourya Basu
A. Magesh
Harshit Yadav
Lav Varshney
71
6
0
10 Apr 2021
Dual-Consistency Semi-Supervised Learning with Uncertainty
  Quantification for COVID-19 Lesion Segmentation from CT Images
Dual-Consistency Semi-Supervised Learning with Uncertainty Quantification for COVID-19 Lesion Segmentation from CT Images
Yanwen Li
Luyang Luo
Huangjing Lin
Hao Chen
Pheng-Ann Heng
93
54
0
07 Apr 2021
Generalization capabilities of translationally equivariant neural
  networks
Generalization capabilities of translationally equivariant neural networks
S. S. Krishna Chaitanya Bulusu
Matteo Favoni
A. Ipp
David I. Müller
Daniel Schuh
AI4CE
92
21
0
26 Mar 2021
Equivariant Point Network for 3D Point Cloud Analysis
Equivariant Point Network for 3D Point Cloud Analysis
Haiwei Chen
Shichen Liu
Weikai Chen
Hao Li
3DPC
94
100
0
25 Mar 2021
ReDet: A Rotation-equivariant Detector for Aerial Object Detection
ReDet: A Rotation-equivariant Detector for Aerial Object Detection
Jiaming Han
Jian Ding
Nan Xue
Guisong Xia
109
545
0
13 Mar 2021
On the geometric and Riemannian structure of the spaces of group
  equivariant non-expansive operators
On the geometric and Riemannian structure of the spaces of group equivariant non-expansive operators
Pasquale Cascarano
Patrizio Frosini
Nicola Quercioli
A. Saki
54
3
0
03 Mar 2021
Abelian Neural Networks
Abelian Neural Networks
Kenshi Abe
Takanori Maehara
Issei Sato
45
2
0
24 Feb 2021
Equivariant neural networks for inverse problems
Equivariant neural networks for inverse problems
E. Celledoni
Matthias Joachim Ehrhardt
Christian Etmann
B. Owren
Carola-Bibiane Schönlieb
Ferdia Sherry
MedImAI4CE
83
27
0
23 Feb 2021
Rotation-Equivariant Deep Learning for Diffusion MRI
Rotation-Equivariant Deep Learning for Diffusion MRI
Philip Muller
Vladimir Golkov
V. Tomassini
Zorah Lähner
DiffMMedIm
72
28
0
13 Feb 2021
Spectral Leakage and Rethinking the Kernel Size in CNNs
Spectral Leakage and Rethinking the Kernel Size in CNNs
Nergis Tomen
Jan van Gemert
AAML
61
19
0
25 Jan 2021
Rotation Equivariant Siamese Networks for Tracking
Rotation Equivariant Siamese Networks for Tracking
D. K. Gupta
Devanshu Arya
E. Gavves
82
37
0
24 Dec 2020
LieTransformer: Equivariant self-attention for Lie Groups
LieTransformer: Equivariant self-attention for Lie Groups
M. Hutchinson
Charline Le Lan
Sheheryar Zaidi
Emilien Dupont
Yee Whye Teh
Hyunjik Kim
138
111
0
20 Dec 2020
Augmentation Inside the Network
Augmentation Inside the Network
Maciej Sypetkowski
Jakub Jasiulewicz
Z. Wojna
OOD
32
2
0
19 Dec 2020
WILDS: A Benchmark of in-the-Wild Distribution Shifts
WILDS: A Benchmark of in-the-Wild Distribution Shifts
Pang Wei Koh
Shiori Sagawa
Henrik Marklund
Sang Michael Xie
Marvin Zhang
...
A. Kundaje
Emma Pierson
Sergey Levine
Chelsea Finn
Percy Liang
OOD
334
1,452
0
14 Dec 2020
The Lottery Tickets Hypothesis for Supervised and Self-supervised
  Pre-training in Computer Vision Models
The Lottery Tickets Hypothesis for Supervised and Self-supervised Pre-training in Computer Vision Models
Tianlong Chen
Jonathan Frankle
Shiyu Chang
Sijia Liu
Yang Zhang
Michael Carbin
Zhangyang Wang
97
123
0
12 Dec 2020
Rotation-Invariant Autoencoders for Signals on Spheres
Rotation-Invariant Autoencoders for Signals on Spheres
Suhas Lohit
Shubhendu Trivedi
MDE
61
5
0
08 Dec 2020
Learning Equivariant Representations
Learning Equivariant Representations
Carlos Esteves
BDL
61
0
0
04 Dec 2020
Kernel-convoluted Deep Neural Networks with Data Augmentation
Kernel-convoluted Deep Neural Networks with Data Augmentation
Minjin Kim
Young-geun Kim
Dongha Kim
Yongdai Kim
M. Paik
36
0
0
04 Dec 2020
Truly shift-invariant convolutional neural networks
Truly shift-invariant convolutional neural networks
Anadi Chaman
Ivan Dokmanić
117
72
0
28 Nov 2020
Equivariant Learning of Stochastic Fields: Gaussian Processes and
  Steerable Conditional Neural Processes
Equivariant Learning of Stochastic Fields: Gaussian Processes and Steerable Conditional Neural Processes
P. Holderrieth
M. Hutchinson
Yee Whye Teh
BDL
110
30
0
25 Nov 2020
Learnable Gabor modulated complex-valued networks for orientation
  robustness
Learnable Gabor modulated complex-valued networks for orientation robustness
Felix Richards
A. Paiement
Xianghua Xie
Elisabeth Sola
Pierre-Alain Duc
35
2
0
23 Nov 2020
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