no code implementations • 9 May 2024 • Shi Yin, Xinyang Pan, Fengyan Wang, Feng Wu, Lixin He
We present both a theoretical and a methodological framework that addresses a critical challenge in applying deep learning to physical systems: the reconciliation of non-linear expressiveness with SO(3)-equivariance in predictions of SO(3)-equivariant quantities, such as the electronic-structure Hamiltonian.