Domain knowledge-assisted materials data anomaly detection towards constructing high-performance machine learning models

Machine learning (ML) is widely applied to accelerate materials design and discovery due to its outperforming capability of data analysis and information extraction. However, experimental and computational errors typically lead to emerging data anomalies, harming the performance of ML models. Most c...

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Главные авторы:	Yue Liu, Shuchang Ma, Zhengwei Yang, Duo Wu, Yali Zhao, Maxim Avdeev, Siqi Shi
Формат:	Artigo
Язык:	Inglês
Опубликовано:	Elsevier 2025-11-01
Серии:	Journal of Materiomics
Предметы:	Machine learning Materials science Data anomaly Domain knowledge
Online-ссылка:	http://www.sciencedirect.com/science/article/pii/S2352847825000565
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