Before revision:  Our method outperforms all reference architectures on 4 out of 8 tasks in the ATOM3D benchmark and broadly improves over rotation-invariant graph neural networks . We also demonstrate that transfer learning can improve performance in learning from macromolecular structure.
After revision:  Our method outperforms all reference architectures on 4 out of 8 tasks in the ATOM3D benchmark , is tied for first on two others, and is competitive with equivariant networks using higher-order representations and spherical harmonic convolutions. In addition, we demonstrate that transfer learning can improve performance in learning from macromolecular structure.