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2106.10044
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Training or Architecture? How to Incorporate Invariance in Neural Networks
18 June 2021
Kanchana Vaishnavi Gandikota
Jonas Geiping
Zorah Lähner
Adam Czapliñski
Michael Moeller
3DPC
OOD
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Papers citing
"Training or Architecture? How to Incorporate Invariance in Neural Networks"
6 / 6 papers shown
Title
Optimization Dynamics of Equivariant and Augmented Neural Networks
Axel Flinth
F. Ohlsson
41
5
0
23 Mar 2023
How Much Data Are Augmentations Worth? An Investigation into Scaling Laws, Invariance, and Implicit Regularization
Jonas Geiping
Micah Goldblum
Gowthami Somepalli
Ravid Shwartz-Ziv
Tom Goldstein
A. Wilson
26
35
0
12 Oct 2022
High-Performance Large-Scale Image Recognition Without Normalization
Andrew Brock
Soham De
Samuel L. Smith
Karen Simonyan
VLM
223
512
0
11 Feb 2021
A Graph-CNN for 3D Point Cloud Classification
Yingxue Zhang
Michael G. Rabbat
3DPC
118
158
0
28 Nov 2018
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
C. Qi
Hao Su
Kaichun Mo
Leonidas J. Guibas
3DH
3DPC
3DV
PINN
222
14,103
0
02 Dec 2016
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
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