Exploring Multi-Fidelity Data in Materials Science: Challenges, Applications, and Optimized Learning Strategies

Exploring Multi-Fidelity Data in Materials Science: Challenges, Applications, and Optimized Learning Strategies

Machine learning techniques offer tremendous potential for optimizing resource allocation in solving real-world problems. However, the emergence of multi-fidelity data introduces new challenges. This paper offers an overview of the definition, applications, data preprocessing methodologies, and lear...

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Bibliographic Details
Main Authors: Ziming Wang, Xiaotong Liu, Haotian Chen, Tao Yang, Yurong He
Format: Article
Language:English
Published: MDPI AG 2023-12-01
Series:Applied Sciences
Subjects:
multi-fidelity data
data noise
machine learning
property prediction
Online Access:https://www.mdpi.com/2076-3417/13/24/13176

Internet

https://www.mdpi.com/2076-3417/13/24/13176

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