fig5

Advances in graph neural networks for alloy design and properties predictions: a review

Figure 5. Comparison of graph-conversion workflows and node-feature construction in (A) the original CGCNN and (B) its improved variant iCGCNN. (A and B) are reproduced from Refs.[23,34] with permission. Copyright © 2018 and © 2020, respectively, American Physical Society. CGCNN: Crystal graph convolutional neural network.

Journal of Materials Informatics
ISSN 2770-372X (Online)
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