Unsupervised manifold learning on ICSD data reveals a low-dimensional embedding that segregates superconductors and predicts critical temperatures across families.
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2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
UNVERDICTED 2representative citing papers
Graphlet-MP supplies graphlet-histogram representations plus an Earth Mover's Distance metric and open code for 149k crystals, enabling data-efficient structural comparisons without end-to-end DFT training.
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Graphlet Histogram Representation Database of Inorganic Crystals
Graphlet-MP supplies graphlet-histogram representations plus an Earth Mover's Distance metric and open code for 149k crystals, enabling data-efficient structural comparisons without end-to-end DFT training.