Quantification of Deep Neural Network Prediction Uncertainties for VVUQ of Machine Learning Models
Author:
Affiliation:
1. North Carolina State University, Burlington Engineering Laboratories, Department of Nuclear Engineering, 2500 Stinson Drive, Raleigh, North Carolina 27695
Publisher
Informa UK Limited
Subject
Nuclear Energy and Engineering
Link
https://www.tandfonline.com/doi/pdf/10.1080/00295639.2022.2123203
Reference38 articles.
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3. Validation and Uncertainty Quantification for Wall Boiling Closure Relations in Multiphase-CFD Solver
4. On the prediction of critical heat flux using a physics-informed machine learning-aided framework
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