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Machine learning of material properties: Predictive and interpretable multilinear models
Machine learning models can provide fast and accurate predictions of material properties but often lack transparency. Interpretability techniques can be used with black box solutions, or alternatively, models can be created that are directly interpretable. We revisit material datasets used in severa...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
American Association for the Advancement of Science
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9075804/ https://www.ncbi.nlm.nih.gov/pubmed/35522750 http://dx.doi.org/10.1126/sciadv.abm7185 |