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Reducing SO(3) Convolutions to SO(2) for Efficient Equivariant GNNs

ICML 2023 · Graph learning › GNN architectures · approach: Physics-inspired GNNs · 28 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use the SO(2)-reduced equivariant convolution in eSCN instead of the SCN message-passing modelOC20 All · OC20 Test, S2EFForce MAE [meV/Å]: 17.7 -> 17.1Helped
Use the SO(2)-reduced equivariant convolution in eSCN instead of SCNOC20 All + MD · OC20 Test, S2EFForce MAE [meV/Å]: 17.2 -> 15.6Helped
Use eSCN instead of GemNet-OCOC22 · OC22 Test, S2EF IDForce MAE [eV/Å]: 29.4 -> 23.8Helped
Use eSCN instead of GemNet-OCOC22 · OC22 Test, S2EF OODForce MAE [eV/Å]: 39.6 -> 35.7Helped
Reduce degree L from 6 to 2 (ablation)eSCN · OC20 2M ValidationForce MAE [meV/Å]: 21.3 -> 26.7Hurt
Reduce degree L from 6 to 4 (ablation)eSCN · OC20 2M ValidationForce MAE [meV/Å]: 21.3 -> 22.2Hurt
Increase degree L from 6 to 8 (ablation)eSCN · OC20 2M ValidationForce MAE [meV/Å]: 21.3 -> 21.3No clear effect
Reduce maximum order M from 2 to 0 (ablation)eSCN · OC20 2M ValidationForce MAE [meV/Å]: 21.3 -> 26.5Hurt
Reduce maximum order M from 2 to 1 (ablation)eSCN · OC20 2M ValidationForce MAE [meV/Å]: 21.3 -> 23.4Hurt
Increase maximum order M from 2 to 3 or 4 (ablation)eSCN · OC20 2M ValidationForce MAE [meV/Å]: 21.3 -> 21.2No clear effect
Reduce layers K from 12 to 4 (ablation)eSCN · OC20 2M ValidationForce MAE [meV/Å]: 21.3 -> 25.6Hurt
Reduce layers K from 12 to 8 (ablation)eSCN · OC20 2M ValidationForce MAE [meV/Å]: 21.3 -> 22.4Hurt

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