Dislocation cartography: Representations and unsupervised classification of dislocation networks with unique fingerprints
Detecting structure in data is the first step to arrive at meaningful representations for systems. This is particularly challenging for evolving dislocation networks evolving as a consequence of plastic deformation of crystalline materials. Our study employs Isomap, a manifold learning technique, to...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
AIP Publishing LLC
2025-03-01
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| Series: | APL Machine Learning |
| Online Access: | http://dx.doi.org/10.1063/5.0224710 |
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