Robust recognition and exploratory analysis of crystal structures via Bayesian deep learning
The present manuscript reports a Bayesian deep-learning approach for the automatic, robust classification of polycrystalline systems of both synthetic and experimental origin. The unsupervised analysis of the internal neural-network representations reveals physically understandable patterns.
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2021-10-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-021-26511-5 |