QT-Net predicts atomic electron populations and multipoles via a new SOAP-cluster held-out test, improving molecular property prediction and recovering QM9 dipole moments from per-atom outputs.
Smooth, exact rotational symmetrization for deep learning on point clouds.Advances in Neural Information Processing Systems, 36:79469–79501
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QT-Net: Rethinking Evaluation of AI Models in Atomic Chemical Space
QT-Net predicts atomic electron populations and multipoles via a new SOAP-cluster held-out test, improving molecular property prediction and recovering QM9 dipole moments from per-atom outputs.