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Spherical CNNs

, , , and . (2018)cite arxiv:1801.10130Comment: Proceedings of the 6th International Conference on Learning Representations (ICLR), 2018.

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Relevance of Rotationally Equivariant Convolutions for Predicting Molecular Properties., , , and . CoRR, (2020)SE(3)-equivariant prediction of molecular wavefunctions and electronic densities., , , , , and . NeurIPS, page 14434-14447. (2021)A General Theory of Equivariant CNNs on Homogeneous Spaces., , and . NeurIPS, page 9142-9153. (2019)Dissecting the Effects of SGD Noise in Distinct Regimes of Deep Learning., , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 30381-30405. PMLR, (2023)Comparing Dynamics: Deep Neural Networks versus Glassy Systems., , , , , , , , and . ICML, volume 80 of Proceedings of Machine Learning Research, page 324-333. PMLR, (2018)A General Theory of Equivariant CNNs on Homogeneous Spaces., , and . CoRR, (2018)Asymptotic learning curves of kernel methods: empirical data v.s. Teacher-Student paradigm., , and . CoRR, (2019)e3nn: Euclidean Neural Networks., and . CoRR, (2022)The jamming transition as a paradigm to understand the loss landscape of deep neural networks., , , , , , and . CoRR, (2018)An end-to-end SE(3)-equivariant segmentation network., , and . CoRR, (2023)