June 11, 2024, 4:47 a.m. | Philipp Misof, Pan Kessel, Jan E. Gerken

cs.LG updates on arXiv.org arxiv.org

arXiv:2406.06504v1 Announce Type: new
Abstract: Equivariant neural networks have in recent years become an important technique for guiding architecture selection for neural networks with many applications in domains ranging from medical image analysis to quantum chemistry. In particular, as the most general linear equivariant layers with respect to the regular representation, group convolutions have been highly impactful in numerous applications. Although equivariant architectures have been studied extensively, much less is known about the training dynamics of equivariant neural networks. Concurrently, …

abstract analysis applications architecture arxiv become chemistry cs.lg domains general image important linear medical networks neural networks quantum quantum chemistry representation type

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