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1807.02547
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3D Steerable CNNs: Learning Rotationally Equivariant Features in Volumetric Data
6 July 2018
Maurice Weiler
Mario Geiger
Max Welling
Wouter Boomsma
Taco S. Cohen
3DPC
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Papers citing
"3D Steerable CNNs: Learning Rotationally Equivariant Features in Volumetric Data"
38 / 38 papers shown
Title
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Permutation Equivariant Neural Networks for Symmetric Tensors
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SE(3)-Equivariant Robot Learning and Control: A Tutorial Survey
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Learning local equivariant representations for quantum operators
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Approximate Equivariance in Reinforcement Learning
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Alec Koppel
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06 Nov 2024
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Zetian Mao
Jiawen Li
Chen Liang
Diptesh Das
Masato Sumita
Koji Tsuda
Kelin Xia
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88
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19 Jun 2024
Steerable Transformers
Soumyabrata Kundu
Risi Kondor
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71
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On the Fourier analysis in the SO(3) space : EquiLoPO Network
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Sergei Grudinin
78
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A Survey of Geometric Graph Neural Networks: Data Structures, Models and Applications
Jiaqi Han
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Liming Wu
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Xiangzhe Kong
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Yu Rong
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120
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01 Mar 2024
Universal Physics Transformers: A Framework For Efficiently Scaling Neural Operators
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Andreas Fürst
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Lukas Gruber
Markus Holzleitner
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19 Feb 2024
Affine Invariance in Continuous-Domain Convolutional Neural Networks
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Johannes Lederer
49
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13 Nov 2023
Automatic Symmetry Discovery with Lie Algebra Convolutional Network
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Robin Walters
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Dashun Wang
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144
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Clebsch-Gordan Nets: a Fully Fourier Space Spherical Convolutional Neural Network
Risi Kondor
Zhen Lin
Shubhendu Trivedi
79
268
0
24 Jun 2018
Why do deep convolutional networks generalize so poorly to small image transformations?
Aharon Azulay
Yair Weiss
70
560
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30 May 2018
CubeNet: Equivariance to 3D Rotation and Translation
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Gabriel J. Brostow
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72
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3D G-CNNs for Pulmonary Nodule Detection
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Taco S. Cohen
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107
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12 Apr 2018
Roto-Translation Covariant Convolutional Networks for Medical Image Analysis
Erik J. Bekkers
Maxime W. Lafarge
M. Veta
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J. Pluim
R. Duits
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173
0
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Intertwiners between Induced Representations (with Applications to the Theory of Equivariant Neural Networks)
Taco S. Cohen
Mario Geiger
Maurice Weiler
60
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HexaConv
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Jorn W. T. Peters
Taco S. Cohen
Max Welling
67
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N-body Networks: a Covariant Hierarchical Neural Network Architecture for Learning Atomic Potentials
Risi Kondor
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73
107
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Tensor field networks: Rotation- and translation-equivariant neural networks for 3D point clouds
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Tess E. Smidt
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Kai Kohlhoff
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On the Generalization of Equivariance and Convolution in Neural Networks to the Action of Compact Groups
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Shubhendu Trivedi
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Spherical CNNs
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Mario Geiger
Jonas Köhler
Max Welling
154
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Covariant Compositional Networks For Learning Graphs
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H. Son
Horace Pan
Brandon M. Anderson
Shubhendu Trivedi
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168
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07 Jan 2018
Learning Steerable Filters for Rotation Equivariant CNNs
Maurice Weiler
Fred Hamprecht
M. Storath
88
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Dynamic Routing Between Capsules
S. Sabour
Nicholas Frosst
Geoffrey E. Hinton
174
4,595
0
26 Oct 2017
Design and Processing of Invertible Orientation Scores of 3D Images for Enhancement of Complex Vasculature
M. Janssen
A. Janssen
Erik J. Bekkers
J. O. Bescós
R. Duits
29
3
0
07 Jul 2017
Deep Sets
Manzil Zaheer
Satwik Kottur
Siamak Ravanbakhsh
Barnabás Póczós
Ruslan Salakhutdinov
Alex Smola
403
2,463
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10 Mar 2017
Equivariance Through Parameter-Sharing
Siamak Ravanbakhsh
J. Schneider
Barnabás Póczós
81
257
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27 Feb 2017
Rotation equivariant vector field networks
Diego Marcos
Michele Volpi
N. Komodakis
D. Tuia
64
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Steerable CNNs
Taco S. Cohen
Max Welling
BDL
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499
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Harmonic Networks: Deep Translation and Rotation Equivariance
Daniel E. Worrall
Stephan J. Garbin
Daniyar Turmukhambetov
Gabriel J. Brostow
124
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GIFT: A Real-time and Scalable 3D Shape Search Engine
S. Bai
X. Bai
Zhichao Zhou
Zhaoxiang Zhang
Longin Jan Latecki
30
281
0
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Group Equivariant Convolutional Networks
Taco S. Cohen
Max Welling
BDL
167
1,934
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Exploiting Cyclic Symmetry in Convolutional Neural Networks
Sander Dieleman
J. Fauw
Koray Kavukcuoglu
115
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Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
Sergey Ioffe
Christian Szegedy
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Adam: A Method for Stochastic Optimization
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