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Pixelizations of Platonic solids such as the cube and icosahedron have been widely used to represent spherical data, from climate records to Cosmic Microwave Background maps.
Regular polytopes
Coxeter, H. S. M · 1973
Earlier work this paper cites.
Permutation groups , volume 163
Dixon, J. D. and Mortimer, B · 1996
Earlier work this paper cites.
An icosahedron-based method for pixelizing the celestial sphere
Tegmark, M · 1996
Earlier work this paper cites.
Representation theory and invariant neural networks
Wood, J. and Shawe-Taylor, J · 1996
Earlier work this paper cites.
Polyhedra
Cromwell, P. R · 1999
Earlier work this paper cites.
Computational group theory
Hiß, G., Holt, D. F., and Newman, M. F · 2007
Earlier work this paper cites.
Divided spheres: Geodesics and the orderly subdivision of the sphere
Popko, E. S · 2012
Earlier work this paper cites.
U-net: Convolutional networks for biomedical image segmentation
Ronneberger, O., Fischer, P., and Brox, T · 2015
Earlier work this paper cites.
Group equivariant convolutional networks
Cohen, T. and Welling, M · 2016
Earlier work this paper cites.
Joint 2d-3d-semantic data for indoor scene understanding
Armeni, I., Sax, S., Zamir, A. R., and Savarese, S · 2017
Earlier work this paper cites.
Spherical convolutions and their application in molecular modelling
Boomsma, W. and Frellsen, J · 2017
Earlier work this paper cites.
Steerable CNNs
Cohen, T. S. and Welling, M · 2017
Earlier work this paper cites.
Rotation equivariant vector field networks
Marcos, D., Volpi, M., Komodakis, N., and Tuia, D · 2017
Earlier work this paper cites.
Segmenting and tracking extreme climate events using neural networks
Mudigonda, M., Kim, S., Mahesh, A., Kahou, S., Kashinath, K., Williams, D., Michalski, V., O’Brien, T., and Prabhat, M · 2017
Earlier work this paper cites.
Pointnet: Deep learning on point sets for 3D classification and segmentation
Qi, C. R., Su, H., Mo, K., and Guibas, L. J · 2017
Earlier work this paper cites.
Equivariance through parameter-sharing
Ravanbakhsh, S., Schneider, J., and Poczos, B · 2017
Earlier work this paper cites.
Dynamic routing between capsules
Sabour, S., Frosst, N., and Hinton, G. E · 2017
Earlier work this paper cites.
Learning spherical convolution for fast features from 360°imagery
Su, Y.-C. and Grauman, K · 2017
Earlier work this paper cites.
Harmonic networks: Deep translation and rotation equivariance
Worrall, D. E., Garbin, S. J., Turmukhambetov, D., and Brostow, G. J · 2017
Cited alongside, same era.
Deep sets
Zaheer, M., Kottur, S., Ravanbakhsh, S., Poczos, B., Salakhutdinov, R. R., and Smola, A. J · 2017
Cited alongside, same era.
Roto-translation covariant convolutional networks for medical image analysis
Bekkers, E. J., Lafarge, M. W., Veta, M., Eppenhof, K. A., Pluim, J. P., and Duits, R · 2018
Cited alongside, same era.
Spherical CNNs
Cohen, T. S., Geiger, M., Köhler, J., and Welling, M · 2018
Cited alongside, same era.
SphereNet: Learning spherical representations for detection and classification in omnidirectional images
Coors, B., Condurache, A. P., and Geiger, A · 2018
Cited alongside, same era.
Learning SO(3) equivariant representations with spherical CNNs
Esteves, C., Allen-Blanchette, C., Makadia, A., and Daniilidis, K · 2018
DeepSphere: Efficient spherical convolutional neural network with HEALPix sampling for cosmological applications
Perraudin, N., Defferrard, M., Kacprzak, T., and Sgier, R · 2019
Later among the works it cites.
General E(2)-equivariant steerable CNNs
Weiler, M. and Cesa, G · 2019
Later among the works it cites.
Orientation-aware semantic segmentation on icosahedron spheres
Zhang, C., Liwicki, S., Smith, W., and Cipolla, R · 2019
Later among the works it cites.
Incidence networks for geometric deep learning
Albooyeh, M., Bertolini, D., and Ravanbakhsh, S · 2020
Later among the works it cites.
Lorentz group equivariant neural network for particle physics
Bogatskiy, A., Anderson, B., Offermann, J., Roussi, M., Miller, D., and Kondor, R · 2020
Later among the works it cites.
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Deep models of interactions across sets
Hartford, J., Graham, D., Leyton-Brown, K., and Ravanbakhsh, S · 2018
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Hexaconv
Hoogeboom, E., Peters, J. W., Cohen, T. S., and Welling, M · 2018
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On the generalization of equivariance and convolution in neural networks to the action of compact groups
Kondor, R. and Trivedi, S · 2018
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Clebsch–gordan nets: a fully Fourier space spherical convolutional neural network
Kondor, R., Lin, Z., and Trivedi, S · 2018
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Group equivariant capsule networks
Lenssen, J. E., Fey, M., and Libuschewski, P · 2018
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Deep learning 3D shapes using alt-az anisotropic 2-sphere convolution
Liu, M., Yao, F., Choi, C., Sinha, A., and Ramani, K · 2018
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Deepsphere: a graph-based spherical CNN
Defferrard, M., Milani, M., Gusset, F., and Perraudin, N · 2020
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On the universality of rotation equivariant point cloud networks
Dym, N. and Maron, H · 2020
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Spin-weighted spherical CNNs
Esteves, C., Makadia, A., and Daniilidis, K · 2020
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SE(3)-transformers: 3D roto-translation equivariant attention networks
Fuchs, F. B., Worrall, D. E., Fischer, V., and Welling, M · 2020
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LieTransformer: Equivariant self-attention for Lie groups
Hutchinson, M., Lan, C. L., Zaidi, S., Dupont, E., Teh, Y. W., and Kim, H · 2020
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Gauge equivariant spherical CNNs, 2020
Kicanaoglu, B., de Haan, P., and Cohen, T · 2020
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Universal equivariant multilayer perceptrons
Ravanbakhsh, S · 2020
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Attentive group equivariant convolutional networks
Romero, D., Bekkers, E., Tomczak, J., and Hoogendoorn, M · 2020
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Equivariant maps for hierarchical structures
Wang, R., Albooyeh, M., and Ravanbakhsh, S · 2020
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Efficient generalized spherical {cnn}s
Cobb, O., Wallis, C. G. R., Mavor-Parker, A. N., Marignier, A., Price, M. A., d’Avezac, M., and McEwen, J · 2021
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Gauge equivariant mesh CNNs: Anisotropic convolutions on geometric graphs
Haan, P. D., Weiler, M., Cohen, T., and Welling, M · 2021
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A wigner-eckart theorem for group equivariant convolution kernels
Lang, L. and Weiler, M · 2021
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Group equivariant stand-alone self-attention for vision
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