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A Statistical Learning Framework for Materials Science: Application to Elastic Moduli of k-nary Inorganic Polycrystalline Compounds
Materials scientists increasingly employ machine or statistical learning (SL) techniques to accelerate materials discovery and design. Such pursuits benefit from pooling training data across, and thus being able to generalize predictions over, k-nary compounds of diverse chemistries and structures....
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| Pubblicato in: | Sci Rep |
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| Autori principali: | , , , , , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Nature Publishing Group
2016
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5046120/ https://ncbi.nlm.nih.gov/pubmed/27694824 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/srep34256 |
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