Crystal Graph Convolutional Neural Networks for an Accurate and Interpretable Prediction of Material Properties

The use of machine learning methods for accelerating the design of crystalline materials usually requires manually constructed feature vectors or complex transformation of atom coordinates to input the crystal structure, which either constrains the model to certain crystal types or makes it difficul...

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Bibliographic Details
Main Authors: Xie, Tian (Contributor), Grossman, Jeffrey C. (Contributor)
Other Authors: Massachusetts Institute of Technology. Department of Materials Science and Engineering (Contributor)
Format: Article
Language:English
Published: American Physical Society, 2018-04-09T17:33:57Z.
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