263 citations · 402 across the 21 of their papers we have counts for
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cond-mat.mtrl-sci2022★ 2 cited
Self-supervised Representations and Node Embedding Graph Neural Networks for Accurate and Multi-scale Analysis of Materials
Jian-Gang Kong, Ke-Lin Zhao, Jian Li +5
Supervised machine learning algorithms, such as graph neural networks (GNN), have successfully predicted material properties. However, the superior performance of GNN usually relie…
cond-mat.mtrl-sci2022★ 9 cited
Self-supervised graph neural networks for accurate prediction of Néel temperature
Jian-Gang Kong, Qing-Xu Li, Jian Li +2
Antiferromagnetic materials are exciting quantum materials with rich physics and great potential for applications. It is highly demanded of the accurate and efficient theoretical m…