Total Magnetization

1 papers with code • 1 benchmarks • 0 datasets

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Greatest papers with code

Crystal Graph Neural Networks for Data Mining in Materials Science

Tony-Y/cgnn Technical report, RIMCS LLC 2019

This paper proposes crystal graph neural networks (CGNNs) that use no bond distances, and introduces a scale-invariant graph coordinator that makes up crystal graphs for the CGNN models to be trained on the dataset based on a theoretical materials database.

Band Gap Formation Energy +2