AWhat changed
Builds rotation-equivariant point convolutions using spherical-harmonic filters and Clebsch–Gordan tensor products, propagating scalar, vector and higher-order geometric features.
Scientific scope
Builds rotation-equivariant point convolutions using spherical-harmonic filters and Clebsch–Gordan tensor products, propagating scalar, vector and higher-order geometric features. This assessment concerns the equivariant architecture and its evaluated 3D/physics tasks. Seven original authors; Thomas and Smidt share contribution. Representation theory and tensor products are inherited mathematics; SO(3) construction is not an automatic O(3), physical-correctness or conservation guarantee. Distinct from the later e3nn software framework.
Evidence
The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. This assessment concerns the equivariant architecture and its evaluated 3D/physics tasks. Seven original authors; Thomas and Smidt share contribution. Representation theory and tensor products are inherited mathematics; SO(3) construction is not an automatic O(3), physical-correctness or conservation guarantee. Distinct from the later e3nn software framework.
Contributors
- Source-listed authors and technical contributors · SCIENCE: Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.
Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.
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