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Homogeneous vector bundles and $G$-equivariant convolutional neural
  networks

Homogeneous vector bundles and GGG-equivariant convolutional neural networks

12 May 2021
J. Aronsson
ArXivPDFHTML

Papers citing "Homogeneous vector bundles and $G$-equivariant convolutional neural networks"

15 / 15 papers shown
Title
Symmetries in Overparametrized Neural Networks: A Mean-Field View
Symmetries in Overparametrized Neural Networks: A Mean-Field View
Javier Maass Martínez
Joaquin Fontbona
FedML
MLT
38
2
0
30 May 2024
EFEM: Equivariant Neural Field Expectation Maximization for 3D Object
  Segmentation Without Scene Supervision
EFEM: Equivariant Neural Field Expectation Maximization for 3D Object Segmentation Without Scene Supervision
Jiahui Lei
Congyue Deng
Karl Schmeckpeper
Leonidas J. Guibas
Kostas Daniilidis
3DPC
24
21
0
27 Mar 2023
Optimization Dynamics of Equivariant and Augmented Neural Networks
Optimization Dynamics of Equivariant and Augmented Neural Networks
Axel Flinth
F. Ohlsson
30
5
0
23 Mar 2023
Computing equivariant matrices on homogeneous spaces for Geometric Deep
  Learning and Automorphic Lie Algebras
Computing equivariant matrices on homogeneous spaces for Geometric Deep Learning and Automorphic Lie Algebras
V. Knibbeler
30
1
0
13 Mar 2023
In Search of Projectively Equivariant Networks
In Search of Projectively Equivariant Networks
Georg Bökman
Axel Flinth
Fredrik Kahl
37
0
0
29 Sep 2022
Unified Fourier-based Kernel and Nonlinearity Design for Equivariant
  Networks on Homogeneous Spaces
Unified Fourier-based Kernel and Nonlinearity Design for Equivariant Networks on Homogeneous Spaces
Yinshuang Xu
Jiahui Lei
Edgar Dobriban
Kostas Daniilidis
23
19
0
16 Jun 2022
ZZ-Net: A Universal Rotation Equivariant Architecture for 2D Point
  Clouds
ZZ-Net: A Universal Rotation Equivariant Architecture for 2D Point Clouds
Georg Bökman
Fredrik Kahl
Axel Flinth
3DPC
26
19
0
30 Nov 2021
Steerable Partial Differential Operators for Equivariant Neural Networks
Steerable Partial Differential Operators for Equivariant Neural Networks
Erik Jenner
Maurice Weiler
15
27
0
18 Jun 2021
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
M. Bronstein
Joan Bruna
Taco S. Cohen
Petar Velivcković
GNN
174
1,104
0
27 Apr 2021
High-Performance Large-Scale Image Recognition Without Normalization
High-Performance Large-Scale Image Recognition Without Normalization
Andrew Brock
Soham De
Samuel L. Smith
Karen Simonyan
VLM
223
512
0
11 Feb 2021
Scaling Up Visual and Vision-Language Representation Learning With Noisy
  Text Supervision
Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision
Chao Jia
Yinfei Yang
Ye Xia
Yi-Ting Chen
Zarana Parekh
Hieu H. Pham
Quoc V. Le
Yun-hsuan Sung
Zhen Li
Tom Duerig
VLM
CLIP
298
3,693
0
11 Feb 2021
A General Theory of Equivariant CNNs on Homogeneous Spaces
A General Theory of Equivariant CNNs on Homogeneous Spaces
Taco S. Cohen
Mario Geiger
Maurice Weiler
MLT
AI4CE
156
308
0
05 Nov 2018
Fully Convolutional Adaptation Networks for Semantic Segmentation
Fully Convolutional Adaptation Networks for Semantic Segmentation
Yiheng Zhang
Zhaofan Qiu
Ting Yao
Dong Liu
Tao Mei
SSeg
OOD
158
349
0
23 Apr 2018
Geometric deep learning on graphs and manifolds using mixture model CNNs
Geometric deep learning on graphs and manifolds using mixture model CNNs
Federico Monti
Davide Boscaini
Jonathan Masci
Emanuele Rodolà
Jan Svoboda
M. Bronstein
GNN
251
1,811
0
25 Nov 2016
Geometric deep learning: going beyond Euclidean data
Geometric deep learning: going beyond Euclidean data
M. Bronstein
Joan Bruna
Yann LeCun
Arthur Szlam
P. Vandergheynst
GNN
247
3,236
0
24 Nov 2016
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