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On-the-fly closed-loop materials discovery via Bayesian active learning
Active learning—the field of machine learning (ML) dedicated to optimal experiment design—has played a part in science as far back as the 18th century when Laplace used it to guide his discovery of celestial mechanics. In this work, we focus a closed-loop, active learning-driven autonomous system on...
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| Publicat a: | Nat Commun |
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| Autors principals: | , , , , , , , , , , , , , , , |
| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
Nature Publishing Group UK
2020
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7686338/ https://ncbi.nlm.nih.gov/pubmed/33235197 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41467-020-19597-w |
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