mlsanityData to 13 Oct 2026

Piecewise Linear Equivariant Maps for Compact Groups

arXiv 2608.21645 ↗First posted 21 Aug 2026math.RT cs.LGcited by 1

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Abstract (arXiv)

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.

Key facts. Cited by 1 paper in the map (data through 13 Oct 2026). Builds on 5 of its 11 references that are in the map. First posted on arXiv 21 Aug 2026.

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5 of 11 references.

References · 5

  1. 2018Tensor field networks: Rotation- and translation-equivariant neural networks for 3D point cloudscited by 739
  2. 2022Functional dimension of feedforward ReLU neural networkscited by 20
  3. 2024A Characterization Theorem for Equivariant Networks with Point-wise Activationscited by 9
  4. 2024Neural reproducing kernel Banach spaces and representer theorems for deep networkscited by 8
  5. 2024Equivariant neural networks and piecewise linear representation theorycited by 3

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