Equivariant Sheaf Neural Networks: Learning Geometric Transport on Graphs.

arXiv:2608.28853v3 Announce Type: replace-cross Abstract: Equivariant graph neural networks provide a principled way to model geometric systems, but efficient first-order architectures remain limited in how vector information can be transformed as it moves acr