Exploring uncertainty in glass phase transitions through machine learning

Machine learning methods have shown significant potential and are widely used in modern physics research. However, the uncertainty linked to machine learning, arising from the opacity of its workflow, demands attention and consideration. This study investigates the application of machine learning mo...

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Veröffentlicht in:	Physica scripta 2024-10, Vol.99 (10), p.1059
Hauptverfasser:	Qi, Rui, Liu, Saihua, Yang, Chengqiao, Sun, Minhua
Format:	Artikel
Sprache:	eng
Schlagworte:	machine learning metallic glass phase transition
Online-Zugang:	Volltext
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