51 citations · 72 across the 3 of their papers we have counts for
3 papers
nucl-th2026
Physics Informed Bayesian Machine Learning of Sparse and Imperfect Nuclear Data
Jiaming Liu, Yang Su, N. C. Shu +2
The prevailing data-driven machine learning has been plagued by the absence of physics knowledge and the scarcity of data. We implement the physics-model informed prior into Bayesi…
nucl-th2021★ 21 cited
Bayesian Data Fusion of Imperfect Fission Yields for Augmented Evaluations
Z. A. Wang, J. C. Pei, Y. J. Chen +4
We demonstrate that Bayesian machine learning can be used to treat the vast amount of experimental fission data which are noisy, incomplete, discrepant, and correlated. As an examp…
nucl-th2021★ 51 cited
Bayesian evaluation of charge yields of fission fragments of 239U
C. Y. Qiao, J. C. Pei, Z. A. Wang +4
Recent experiments [Phys. Rev. Lett. 123, 092503(2019); Phys. Rev. Lett. 118, 222501 (2017)] have made remarkable progress in measurements of the isotopic fission-fragment yields o…