Equivariant Geometric Scattering Networks via Vector Diffusion Wavelets
David R. Johnson, Rishabh Anand, Smita Krishnaswamy, Michael Perlmutter
公開日: 2025/10/1
Abstract
We introduce a novel version of the geometric scattering transform for geometric graphs containing scalar and vector node features. This new scattering transform has desirable symmetries with respect to rigid-body roto-translations (i.e., $SE(3)$-equivariance) and may be incorporated into a geometric GNN framework. We empirically show that our equivariant scattering-based GNN achieves comparable performance to other equivariant message-passing-based GNNs at a fraction of the parameter count.