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Learning equivariant representations is a promising way to reduce sample and model complexity and improve the generalization performance of deep neural networks.
“Quaternion Equivariant Capsule Networks for 3d Point Clouds”
Yongheng Zhao, Tolga Birdal, Jan Lenssen, Emanuele Menegatti, Leonidas Guibas and Federico Tombari · 1912
Earlier work this paper cites.
“3D ShapeNets: A Deep Representation for Volumetric Shapes”
Zhirong Wu, Shuran Song, Aditya Khosla, Fisher Yu, Linguang Zhang, Xiaoou Tang and Jianxiong Xiao · 1920
Earlier work this paper cites.
“Note on the Bondi-Metzner-Sachs Group”
Ezra Newman and Roger Penrose · 1966
Earlier work this paper cites.
“Representation of Lie Groups and Special Functions”
N.. Vilenkin and A.. Klimyk · 1991
Earlier work this paper cites.
“Computing Fourier transforms and convolutions on the 2-sphere”
James Driscoll and Dennis Healy · 1994
Earlier work this paper cites.
“Fourier transform summation of Legendre series and D-functions”
Torben Risbo · 1996
Earlier work this paper cites.
“Theoretical Aspects of Group Equivariant Neural Networks”
Carlos Esteves · 2004
Earlier work this paper cites.
“Rotation recovery from spherical images without correspondences”
A. Makadia and K. Daniilidis · 2006
Earlier work this paper cites.
“An empirical evaluation of deep architectures on problems with many factors of variation”
Hugo Larochelle, Dumitru Erhan, Aaron Courville, James Bergstra and Yoshua Bengio · 2007
Earlier work this paper cites.
“FFTs on the rotation group”
Peter Kostelec and Daniel Rockmore · 2008
Earlier work this paper cites.
“Fast, exact (but unstable) spin spherical harmonic transforms”
Jason McEwen · 2008
Earlier work this paper cites.
“Fast and Exact Spin-s Spherical Harmonic Transforms”
Kevin. Huffenberger and Benjamin. Wandelt · 2010
Earlier work this paper cites.
“MNIST handwritten digit database”, 2010
Yann LeCun, Corinna Cortes and CJ Burges · 2010
Earlier work this paper cites.
“3-D spinors, spin-weighted functions and their applications”
Gerardo del Castillo · 2012
Earlier work this paper cites.
“Angular velocity of gravitational radiation from precessing binaries and the corotating frame”
Michael Boyle · 2013
Earlier work this paper cites.
“Deep symmetry networks”
Robert Gens and Pedro Domingos · 2014
Earlier work this paper cites.
“Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift”
Sergey Ioffe and Christian Szegedy · 2015
Earlier work this paper cites.
“Adam: A Method for Stochastic Optimization”
Diederik. Kingma and Jimmy Ba · 2015
Earlier work this paper cites.
“U-Net: Convolutional Networks for Biomedical Image Segmentation”
Olaf Ronneberger, Philipp Fischer and Thomas Brox · 2015
Cited alongside, same era.
“How should spin-weighted spherical functions be defined?”
Michael Boyle · 2016
Cited alongside, same era.
“Group equivariant convolutional networks”
Taco Cohen and Max Welling · 2016
Cited alongside, same era.
“Exploiting Cyclic Symmetry in Convolutional Neural Networks”
Sander Dieleman, Jeffrey Fauw and Koray Kavukcuoglu · 2016
Cited alongside, same era.
“A course in abstract harmonic analysis”
Gerald Folland · 2016
Cited alongside, same era.
“Deep Residual Learning for Image Recognition”
Kaiming He, Xiangyu Zhang, Shaoqing Ren and Jian Sun · 2016
Cited alongside, same era.
“On the Generalization of Equivariance and Convolution in Neural Networks to the Action of Compact Groups”
Risi Kondor and Shubhendu Trivedi · 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 Kearnes, Lusann Yang, Li Li, Kai Kohlhoff and Patrick Riley · 2018
Later among the works it cites.
“3D Steerable CNNs: Learning Rotationally Equivariant Features in Volumetric Data”
Maurice Weiler, Mario Geiger, Max Welling, Wouter Boomsma and Taco Cohen · 2018
Later among the works it cites.
“Learning Steerable Filters for Rotation Equivariant CNNs”
Maurice Weiler, Fred. Hamprecht and Martin Storath · 2018
Later among the works it cites.
“3D G-CNNs for Pulmonary Nodule Detection”
Marysia Winkels and Taco Cohen · 2018
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“Rethinking the Inception Architecture for Computer Vision”
Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe, Jon Shlens and Zbigniew Wojna · 2016
Cited alongside, same era.
“Joint 2D-3D-Semantic Data for Indoor Scene Understanding”
Iro Armeni, Sasha Sax, Amir Zamir and Silvio Savarese · 2017
Cited alongside, same era.
“Steerable CNNs”
Taco. Cohen and Max Welling · 2017
Cited alongside, same era.
“Warped convolutions: Efficient invariance to spatial transformations”
Joao Henriques and Andrea Vedaldi · 2017
Cited alongside, same era.
“Rotation Equivariant Vector Field Networks”
Diego Marcos, Michele Volpi, Nikos Komodakis and Devis Tuia · 2017
Cited alongside, same era.
“Harmonic networks: Deep translation and rotation equivariance”
Daniel Worrall, Stephan Garbin, Daniyar Turmukhambetov and Gabriel Brostow · 2017
Cited alongside, same era.
“Cubenet: Equivariance to 3d rotation and translation”
Daniel Worrall and Gabriel Brostow · 2018
Later among the works it cites.
“Cormorant: Covariant Molecular Neural Networks”
Brandon. Anderson, Truong-Son Hy and Risi Kondor · 2019
Later among the works it cites.
“Gauge Equivariant Convolutional Networks and the Icosahedral CNN”
Taco Cohen, Maurice Weiler, Berkay Kicanaoglu and Max Welling · 2019
Later among the works it cites.
“A General Theory of Equivariant CNNs on Homogeneous Spaces”
Taco Cohen, Mario Geiger and Maurice Weiler · 2019
Later among the works it cites.
“Equivariant Multi-View Networks”
Carlos Esteves, Yinshuang Xu, Christine Allen-Blanchette and Kostas Daniilidis · 2019
Later among the works it cites.
“Spherical CNNs on Unstructured Grids”
Chiyu Jiang, Jingwei Huang, Karthik Kashinath, Prabhat, Philip Marcus and Matthias Nießner · 2019
Later among the works it cites.
“DeepSphere: Efficient spherical convolutional neural network with HEALPix sampling for cosmological applications”
Nathanaël Perraudin, Michaël Defferrard, Tomasz Kacprzak and Raphael Sgier · 2019
Later among the works it cites.
“General E(2)-Equivariant Steerable CNNs”
Maurice Weiler and Gabriele Cesa · 2019
Later among the works it cites.
“Deep Scale-spaces: Equivariance Over Scale”
Daniel. Worrall and Max Welling · 2019
Later among the works it cites.
“Orientation-Aware Semantic Segmentation on Icosahedron Spheres”
Chao Zhang, Stephan Liwicki, William Smith and Roberto Cipolla · 2019
Later among the works it cites.
“B-Spline CNNs on Lie groups”
Erik. Bekkers · 2020
Closest in time.
“Gauge Equivariant Spherical {CNN}s”, 2020
Berkay Kicanaoglu, Pim de Haan and Taco Cohen · 2020
Closest in time.