Equivariant Geometric Scattering Networks via Vector Diffusion Wavelets
Dave Johnson ⋅ Rishabh Anand ⋅ Smita Krishnaswamy ⋅ Michael Perlmutter
2025 Poster
in
Workshop: New Perspectives in Graph Machine Learning
in
Workshop: New Perspectives in Graph Machine Learning
Abstract
We introduce a novel version of the geometric scattering transform for geometric graphs with both scalar- and vector-valued node features. We show that this new scattering transform has desirable symmetries with respect to rotations in Euclidean space and may be incorporated into a geometric GNN, which achieves comparable performance to other equivariant GNNs at a fraction of the parameter count.
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