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Identifying domains of applicability of machine learning models for materials science
Although machine learning (ML) models promise to substantially accelerate the discovery of novel materials, their performance is often still insufficient to draw reliable conclusions. Improved ML models are therefore actively researched, but their design is currently guided mainly by monitoring the...
Autores principales: | Sutton, Christopher, Boley, Mario, Ghiringhelli, Luca M., Rupp, Matthias, Vreeken, Jilles, Scheffler, Matthias |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7474068/ https://www.ncbi.nlm.nih.gov/pubmed/32887879 http://dx.doi.org/10.1038/s41467-020-17112-9 |
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