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A universal similarity based approach for predictive uncertainty quantification in materials science

Immense effort has been exerted in the materials informatics community towards enhancing the accuracy of machine learning (ML) models; however, the uncertainty quantification (UQ) of state-of-the-art algorithms also demands further development. Most prominent UQ methods are model-specific or are rel...

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Detalles Bibliográficos
Autores principales: Korolev, Vadim, Nevolin, Iurii, Protsenko, Pavel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9440040/
https://www.ncbi.nlm.nih.gov/pubmed/36056050
http://dx.doi.org/10.1038/s41598-022-19205-5

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