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Reliable Uncertainty Estimation for Machine-Learned Multigroup Cross Sections Without Retraining

Nichols, Joshua et al.
arXiv (All) · Papers
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computational-physicsi-2-1
Uncertainty quantification in machine learning models is essential for nuclear energy applications. While machine learning models can make both uncertainty and point predictions, these models are often significantly more difficult to train jointly than models that make point predictions alone. Split
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