Integrating multiple materials science projects in a single neural network
Traditionally, machine learning for materials science is based on database-specific models and is limited in the number of predictable parameters. Here, a versatile graph-based neural network can integrate multiple data sources, allowing the prediction of more than 40 parameters simultaneously.
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Publishing Group
2020-07-01
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| Series: | Communications Materials |
| Online Access: | https://doi.org/10.1038/s43246-020-00052-8 |