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Recent work by Cohen \emph{et al.} has achieved state-of-the-art results for learning spherical images in a rotation invariant way by using ideas from group representation theory and noncommutative harmonic analysis.
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Learning invariant representations of molecules for atomization energy prediction
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Deep Symmetry Networks
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Geodesic convolutional neural networks on riemannian manifolds
J. Masci, D. Boscaini, M. M. Bronstein, and P. Vandergheynst · 2015
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A. X. Chang, T. Funkhouser, L. Guibas, P. Hanrahan, Q. Huang, Z. Li, S. Savarese, M. Savva, S. Song, H. Su, J. Xiao, L. Yi, and F. Yu · 2015
Learning SO(3) Equivariant Representations with Spherical CNNs
C. Esteves, C. Allen-Blanchette, A. Makadia, and K. Daniilidis · 2017
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Pano2vid: Automatic cinematography for watching 360 ∘
Y-C Su, D. Jayaraman, and K. Grauman · 2017
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Graph-Based Classification of Omnidirectional Images
R. Khasanova and P. Frossard · 2017
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Spherical convolutions and their application in molecular modelling
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Polar Transformer Networks
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Group equivariant convolutional networks
T. S. Cohen and M. Welling · 2016
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Harmonic Networks: Deep Translation and Rotation Equivariance
D. E. Worrall, S. J. Garbin, D. Turmukhambetov, and G. J. Brostow · 2016
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Geometric deep learning on graphs and manifolds using mixture model cnns
F. Monti, D. Boscaini, J. Masci, E. Rodola, J. Svoboda, and M. M. Bronstein · 2016
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Local group invariant representations via orbit embeddings
A. Raj, A. Kumar, Y. Mroueh, and P.T. Fletcher et al · 2016
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Steerable cnns
T. S. Cohen and M. Welling · 2017
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Equivariance through parameter-sharing
S. Ravanbakhsh, J. Schneider, and B. Poczos · 2017
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M. Zaheer, S. Kottur, S. Ravanbakhsh, B. Poczos, R. Salakhutdinov, , and A. Smola · 2017
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Large-scale 3d shape retrieval from shapenet core55
M. Savva, F. Yu, H. Su, A. Kanezaki, T. Furuya, R. Ohbuchi, Z. Zhou, R. Yu, S. Bai, X. Bai, M. Aono, A. Tatsuma, S. Thermos, A. Axenopoulos, G. Th. Papadopoulos, P. Daras, X. Deng, Z. Lian, B. Li, H. Johan, Y. Lu, and S. Mk · 2017
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Spherical CNNs
T. S. Cohen, M. Geiger, J. Köhler, and M. Welling · 2018
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On the generalization of equivariance and convolution in neural networks to the action of compact groups
R. Kondor and S. Trivedi · 2018
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Tensor field networks: Rotation- and translation-equivariant neural networks for 3d point clouds
N. Thomas, T. Smidt, S. Kearnes, L. Yang, L. Li, K. Kohlhoff, and P. Riley · 2018
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N-body networks: a covariant hierarchical neural network architecture for learning atomic potentials
R. Kondor · 2018
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