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Autonomous materials discovery driven by Gaussian process regression with inhomogeneous measurement noise and anisotropic kernels

A majority of experimental disciplines face the challenge of exploring large and high-dimensional parameter spaces in search of new scientific discoveries. Materials science is no exception; the wide variety of synthesis, processing, and environmental conditions that influence material properties gi...

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Bibliografiska uppgifter
I publikationen:Sci Rep
Huvudupphovsmän: Noack, Marcus M., Doerk, Gregory S., Li, Ruipeng, Streit, Jason K., Vaia, Richard A., Yager, Kevin G., Fukuto, Masafumi
Materialtyp: Artigo
Språk:Inglês
Publicerad: Nature Publishing Group UK 2020
Ämnen:
Länkar:https://ncbi.nlm.nih.gov/pmc/articles/PMC7573639/
https://ncbi.nlm.nih.gov/pubmed/33077759
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41598-020-74394-1
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