Learning Long-Range Representations with Equivariant Messages

arXiv:2507.19382v2 Announce Type: replace Abstract: Machine learning interatomic potentials trained on first-principles reference data are becoming valuable tools for computational physics, biology, and chemistry. Equivariant message-passing neural networks, including transfor...

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