Self-supervised probabilistic models for exploring shape memory alloys
Abstract Recent advancements in machine learning (ML) have revolutionized the field of high-performance materials design. However, developing robust ML models to decipher intricate structure-property relationships in materials remains challenging, primarily due to the limited availability of labeled...
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| Auteurs principaux: | , , , , , , |
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| Format: | Artigo |
| Langue: | Inglês |
| Publié: |
Nature Portfolio
2024-08-01
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| Collection: | npj Computational Materials |
| Accès en ligne: | https://doi.org/10.1038/s41524-024-01379-3 |
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