Ab initio parametrization of distributed polarizable force fields via per-atom polarizability tensors and a message-passing GNN for scalable prediction on small organic molecules.
arXiv preprint arXiv:2405.15389 (2024)
2 Pith papers cite this work. Polarity classification is still indexing.
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A tensor-channel equivariant GNN based on PaiNN propagates symmetric rank-2 tensor features during message passing and achieves lower full-tensor and anisotropic error than readout-only and MACE baselines on QM7-X geometries.
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Ab initio parametrization of distributed polarizable force fields
Ab initio parametrization of distributed polarizable force fields via per-atom polarizability tensors and a message-passing GNN for scalable prediction on small organic molecules.
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Tensor Channel Equivariant Graph Neural Networks for Molecular Polarizability Prediction
A tensor-channel equivariant GNN based on PaiNN propagates symmetric rank-2 tensor features during message passing and achieves lower full-tensor and anisotropic error than readout-only and MACE baselines on QM7-X geometries.