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The big empirical success of group equivariant networks has led in recent years to the sprouting of a great variety of equivariant network architectures.
Linear representations of finite groups
Jean-Pierre Serre · 1977
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An analysis of single-layer networks in unsupervised feature learning
Adam Coates, Andrew Ng, and Honglak Lee · 2011
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Combined scattering for rotation invariant texture analysis
Laurent Sifre and Stéphane Mallat · 2012
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Rotation, scaling and deformation invariant scattering for texture discrimination
Laurent Sifre and Stéphane Mallat · 2013
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Invariant scattering convolution networks
Joan Bruna and Stéphane Mallat · 2013
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Rigid-motion scattering for texture classification
Laurent Sifre and Stéphane Mallat · 2014
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Spectral Networks and Deep Locally Connected Networks on Graphs
J. Bruna, W. Zaremba, A. Szlam, and Y. LeCun · 2014
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Deep roto-translation scattering for object classification
Edouard Oyallon and Stéphane Mallat · 2015
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Geodesic convolutional neural networks on Riemannian manifolds
Jonathan Masci, Davide Boscaini, Michael M. Bronstein, and Pierre Vandergheynst · 2015
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Learning class-specific descriptors for deformable shapes using localized spectral convolutional networks
Davide Boscaini, Jonathan Masci, Simone Melzi, Michael M. Bronstein, Umberto Castellani, and Pierre Vandergheynst · 2015
Earlier work this paper cites.
Group equivariant convolutional networks
Taco S. Cohen and Max Welling · 2016
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Exploiting cyclic symmetry in convolutional neural networks
Sander Dieleman, Jeffrey De Fauw, and Koray Kavukcuoglu · 2016
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Fast and accurate deep network learning by exponential linear units (ELUs)
Djork-Arné Clevert, Thomas Unterthiner, and Sepp Hochreiter · 2016
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Learning rotation invariant convolutional filters for texture classification
Diego Marcos, Michele Volpi, and Devis Tuia · 2016
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Ti-pooling: Transformation-invariant pooling for feature learning in convolutional neural networks
Dmitry Laptev, Nikolay Savinov, Joachim M. Buhmann, and Marc Pollefeys · 2016
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Wide residual networks
Sergey Zagoruyko and Nikos Komodakis · 2016
Cited alongside, same era.
Steerable CNNs
Taco S. Cohen and Max Welling · 2017
Cited alongside, same era.
Harmonic networks: Deep translation and rotation equivariance
Daniel E. Worrall, Stephan J. Garbin, Daniyar Turmukhambetov, and Gabriel J. Brostow · 2017
Cited alongside, same era.
Rotation equivariant vector field networks
Diego Marcos, Michele Volpi, Nikos Komodakis, and Devis Tuia · 2017
Cited alongside, same era.
Dynamic routing between capsules
Sara Sabour, Nicholas Frosst, and Geoffrey E. Hinton · 2017
Cited alongside, same era.
Improved regularization of convolutional neural networks with cutout
Terrance DeVries and Graham W. Taylor · 2017
Cited alongside, same era.
Learning SO(3) equivariant representations with spherical CNNs
Carlos Esteves, Christine Allen-Blanchette, Ameesh Makadia, and Kostas Daniilidis · 2018
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Nathanaël Perraudin, Michaël Defferrard, Tomasz Kacprzak, and Raphael Sgier · 2018
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Multi-directional geodesic neural networks via equivariant convolution
Adrien Poulenard and Maks Ovsjanikov · 2018
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3D G-CNNs for pulmonary nodule detection
Marysia Winkels and Taco S. Cohen · 2018
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Cubenet: Equivariance to 3D rotation and translation
Daniel E. Worrall and Gabriel J. Brostow · 2018
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N-body networks: a covariant hierarchical neural network architecture for learning atomic potentials
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3D steerable CNNs: Learning rotationally equivariant features in volumetric data
Maurice Weiler, Mario Geiger, Max Welling, Wouter Boomsma, and Taco S. Cohen · 2018
Cited alongside, same era.
Taco S. Cohen, Mario Geiger, and Maurice Weiler · 2018
Cited alongside, same era.
A general theory of equivariant CNNs on homogeneous spaces
Taco S. Cohen, Mario Geiger, and Maurice Weiler · 2018
Cited alongside, same era.
Learning steerable filters for rotation equivariant CNNs
Maurice Weiler, Fred A. Hamprecht, and Martin Storath · 2018
Cited alongside, same era.
HexaConv
Emiel Hoogeboom, Jorn W. T. Peters, Taco S. Cohen, and Max Welling · 2018
Cited alongside, same era.
Roto-translation covariant convolutional networks for medical image analysis
Erik J. Bekkers, Maxime W Lafarge, Mitko Veta, Koen A.J. Eppenhof, Josien P.W. Pluim, and Remco Duits · 2018
Cited alongside, same era.
Risi Kondor · 2018
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Land cover mapping at very high resolution with rotation equivariant CNNs: Towards small yet accurate models
Diego Marcos, Michele Volpi, Benjamin Kellenberger, and Devis Tuia · 2018
Later among the works it cites.
Rotation equivariant CNNs for digital pathology
Bastiaan S. Veeling, Jasper Linmans, Jim Winkens, Taco S. Cohen, and Max Welling · 2018
Later among the works it cites.
Tensor field networks: Rotation- and translation-equivariant neural networks for 3d point clouds
Nathaniel Thomas, Tess Smidt, Steven M. Kearnes, Lusann Yang, Li Li, Kai Kohlhoff, and Patrick Riley · 2018
Later among the works it cites.
Matrix capsules with EM routing
Geoffrey Hinton, Nicholas Frosst, and Sabour Sara · 2018
Later among the works it cites.
Gauge equivariant convolutional networks and the icosahedral CNN
Taco S. Cohen, Maurice Weiler, Berkay Kicanaoglu, and Max Welling · 2019
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Spherical CNNs on unstructured grids
Chiyu Jiang, Jingwei Huang, Karthik Kashinath, Prabhat, Philip Marcus, and Matthias Niessner · 2019
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Learning to convolve: A generalized weight-tying approach
Nichita Diaconu and Daniel Worrall · 2019
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Cormorant: Covariant molecular neural networks
Brandon Anderson, Truong-Son Hy, and Risi Kondor · 2019
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Autoaugment: Learning augmentation strategies from data
Ekin D. Cubuk, Barret Zoph, Dandelion Mane, Vijay Vasudevan, and Quoc V. Le · 2019
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