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Graph & Geometric LearningEquivariant Neural Network2608.21645

Piecewise Linear Equivariant Maps for Compact Groups

Valeriano Aiello

math.RT cs.LG

Abstract

Motivated by equivariant neural networks, we study piecewise linear equivariant maps between finite-dimensional real representations of compact groups. We show that all genuinely non-linear piecewise linear behaviour is confined to the subspaces on which the identity component of the group acts trivially, while equivariance forces linearity on the corresponding orthogonal complements. As a consequence, we obtain a compact-group analogue of the finite-group existence criterion of Gibson--Tubbenhauer--Williamson for non-zero equivariant piecewise linear maps between irreducible representations, with the identity component giving rise to a rigidity phenomenon absent from the finite-group case.

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Classified with taxonomy v2 on Sat, 5 Sept 2026.

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