Symmetry group equivariant architectures for physics
Physical theories grounded in mathematical symmetries are an essential component of our
understanding of a wide range of properties of the universe. Similarly, in the domain of
machine learning, an awareness of symmetries such as rotation or permutation invariance
has driven impressive performance breakthroughs in computer vision, natural language
processing, and other important applications. In this report, we argue that both the physics
community and the broader machine learning community have much to understand and …
understanding of a wide range of properties of the universe. Similarly, in the domain of
machine learning, an awareness of symmetries such as rotation or permutation invariance
has driven impressive performance breakthroughs in computer vision, natural language
processing, and other important applications. In this report, we argue that both the physics
community and the broader machine learning community have much to understand and …
[CITATION][C] Symmetry group equivariant architectures for physics, in 2022 Snowmass Summer Study (2022)
A Bogatskiy - arXiv preprint arXiv:2203.06153
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