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3D Steerable CNNs: Learning Rotationally Equivariant Features in Volumetric Data.

, , , , and . NeurIPS, page 10402-10413. (2018)

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Teacher-Student Curriculum Learning., , , and . CoRR, (2017)A General Theory of Equivariant CNNs on Homogeneous Spaces., , and . CoRR, (2018)3D Steerable CNNs: Learning Rotationally Equivariant Features in Volumetric Data., , , , and . NeurIPS, page 10402-10413. (2018)Learning the Irreducible Representations of Commutative Lie Groups., and . ICML, volume 32 of JMLR Workshop and Conference Proceedings, page 1755-1763. JMLR.org, (2014)Group Equivariant Convolutional Networks., and . ICML, volume 48 of JMLR Workshop and Conference Proceedings, page 2990-2999. JMLR.org, (2016)Rotation Equivariant CNNs for Digital Pathology., , , , and . MICCAI (2), volume 11071 of Lecture Notes in Computer Science, page 210-218. Springer, (2018)Guest Editorial: Non-Euclidean Machine Learning., , , , , , , , and . IEEE Trans. Pattern Anal. Mach. Intell., 44 (2): 723-726 (2022)Adversarial Distortion for Learned Video Compression., , , and . CVPR Workshops, page 640-644. Computer Vision Foundation / IEEE, (2020)Convolutional Networks for Spherical Signals., , , and . CoRR, (2017)Harmonic Exponential Families on Manifolds., and . ICML, volume 37 of JMLR Workshop and Conference Proceedings, page 1757-1765. JMLR.org, (2015)