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Euclidean Symmetry and Equivariance in Machine Learning

Abstract

© 2020 Elsevier Inc. Understanding the role of symmetry in the physical sciences is critical for choosing an appropriate machine-learning method. While invariant models are the most prevalent symmetry-aware models, equivariant models such as Euclidean neural networks more faithfully represent physical interactions and are ready to take on challenges across the physical sciences.

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