Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals

@article{Chen2018GraphNA,
  title={Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals},
  author={Chi Chen and Weike Ye and Yunxing Zuo and Chen Zheng and Shyue Ping Ong},
  journal={arXiv: Materials Science},
  year={2018}
}
  • Chi Chen, Weike Ye, +2 authors Shyue Ping Ong
  • Published 2018
  • Physics, Materials Science
  • arXiv: Materials Science
  • Graph networks are a new machine learning (ML) paradigm that supports both relational reasoning and combinatorial generalization. Here, we develop, for the first time, universal MatErials Graph Network (MEGNet) models for accurate property prediction in both molecules and crystals. We demonstrate that our MEGNet models significantly outperform prior ML models in 11 out of 13 properties of the QM9 molecule data set. Furthermore, a single-task unified MEGNet model can accurately predict the… CONTINUE READING

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