SPHNet uses learned sparse gates to prune atom pairs and tensor-product combinations, cutting training cost up to 7.1x while matching or improving Hamiltonian prediction accuracy on QH9, PubChemQH, and MD17.
(A) The Vectorial Node Interaction Block, which uses a long-short range message-passing mechanism
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Efficient and Scalable Density Functional Theory Hamiltonian Prediction through Adaptive Sparsity
SPHNet uses learned sparse gates to prune atom pairs and tensor-product combinations, cutting training cost up to 7.1x while matching or improving Hamiltonian prediction accuracy on QH9, PubChemQH, and MD17.