Training or Architecture? How to Incorporate Invariance in Neural
Networks

Training or Architecture? How to Incorporate Invariance in Neural Networks

18 June 2021

Kanchana Vaishnavi Gandikota

Adam Czapliñski

Michael Moeller

Papers citing "Training or Architecture? How to Incorporate Invariance in Neural Networks"

17 / 17 papers shown

Title
High-Performance Large-Scale Image Recognition Without Normalization Andrew Brock Soham De Samuel L. Smith Karen Simonyan VLM 276 520 0 11 Feb 2021
General $E(2)$ -Equivariant Steerable CNNs Maurice Weiler Gabriele Cesa 113 524 0 19 Nov 2019
Invariance-inducing regularization using worst-case transformations suffices to boost accuracy and spatial robustness Fanny Yang Zuowen Wang C. Heinze-Deml 100 42 0 26 Jun 2019
OperatorNet: Recovering 3D Shapes From Difference Operators Ruqi Huang Marie-Julie Rakotosaona Panos Achlioptas Leonidas Guibas M. Ovsjanikov 38 20 0 24 Apr 2019
Equivariant Transformer Networks Kai Sheng Tai Peter Bailis Gregory Valiant ViT 76 71 0 25 Jan 2019
3D Point Capsule Networks Yongheng Zhao Tolga Birdal Haowen Deng Federico Tombari 3DPC 54 337 0 27 Dec 2018
A Graph-CNN for 3D Point Cloud Classification Yingxue Zhang Michael G. Rabbat 3DPC 170 158 0 28 Nov 2018
PPF-FoldNet: Unsupervised Learning of Rotation Invariant 3D Local Descriptors Haowen Deng Tolga Birdal Slobodan Ilic 3DPC 88 391 0 30 Aug 2018
Tensor field networks: Rotation- and translation-equivariant neural networks for 3D point clouds Nathaniel Thomas Tess E. Smidt S. Kearnes Lusann Yang Li Li Kai Kohlhoff Patrick F. Riley 3DPC 83 970 0 22 Feb 2018
Rotation equivariant vector field networks Diego Marcos Michele Volpi N. Komodakis D. Tuia 64 270 0 29 Dec 2016
Harmonic Networks: Deep Translation and Rotation Equivariance Daniel E. Worrall Stephan J. Garbin Daniyar Turmukhambetov Gabriel J. Brostow 124 710 0 14 Dec 2016
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation C. Qi Hao Su Kaichun Mo Leonidas Guibas 3DH 3DPC 3DV PINN 481 14,309 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 412 1,820 0 25 Nov 2016
Warped Convolutions: Efficient Invariance to Spatial Transformations João F. Henriques Andrea Vedaldi 46 116 0 14 Sep 2016
Learning rotation invariant convolutional filters for texture classification Diego Marcos Michele Volpi D. Tuia 64 148 0 22 Apr 2016
Group Equivariant Convolutional Networks Taco S. Cohen Max Welling BDL 167 1,934 0 24 Feb 2016
Spatial Transformer Networks Max Jaderberg Karen Simonyan Andrew Zisserman Koray Kavukcuoglu 297 7,384 0 05 Jun 2015