An O(L^3) algorithm computes contracted Clebsch-Gordan tensor products for equivariant ML potentials using a structured angular grid and spherical Poisson bracket to handle parity-odd terms at fixed CP rank.
Reducing SO(3) convolutions to SO(2) for efficient equivariant GNNs
2 Pith papers cite this work. Polarity classification is still indexing.
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Velocityformer achieves 35% higher velocity correlation than linear theory by matching graph transformer inductive bias to the line-of-sight broken symmetry and conditioning on long-wavelength physics, while training efficiently on only four low-fidelity simulations.
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Fast contracted Clebsch--Gordan tensor products for equivariant graph neural networks
An O(L^3) algorithm computes contracted Clebsch-Gordan tensor products for equivariant ML potentials using a structured angular grid and spherical Poisson bracket to handle parity-odd terms at fixed CP rank.
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Velocityformer: Broken-Symmetry-Matched Equivariant Graph Transformers for Cosmological Velocity Reconstruction
Velocityformer achieves 35% higher velocity correlation than linear theory by matching graph transformer inductive bias to the line-of-sight broken symmetry and conditioning on long-wavelength physics, while training efficiently on only four low-fidelity simulations.