An investigation on machine learning predictive accuracy improvement and uncertainty reduction using VAE-based data augmentation

The confluence of ultrafast computers with large memory, rapid progress in Machine Learning (ML) algorithms, and the availability of large datasets place multiple engineering fields at the threshold of dramatic progress. However, a unique challenge in nuclear engineering is data scarcity because exp...

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Bibliographic Details

Published in:	Nuclear engineering and design Vol. 445; p. 114433
Main Authors:	Alsafadi, Farah, Yaseen, Mahmoud, Wu, Xu
Format:	Journal Article
Language:	English
Published:	United States Elsevier B.V 15.12.2025 Elsevier BV
Subjects:	Bayesian neural network Conformal prediction Data augmentation Uncertainty quantification Variational autoencoders Variational autoencoders Uncertainty quantification Data augmentation Bayesian neural network Conformal prediction
ISSN:	0029-5493
Online Access:	Get full text
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