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Cited article:

Bayesian neural network evaluation method on the neutron-induced fission product yields of $$^{232}$$Th

Chun-Yuan Qiao, Ya-Xuan Wang, Chun-Wang Ma, Jun-Chen Pei and Yong-Jing Chen
Nuclear Science and Techniques 37 (3) (2026)
https://doi.org/10.1007/s41365-025-01858-2

Verification of neutron-induced fission product yields evaluated by a tensor decompsition model in transport-burnup simulations

Qu-Fei Song, Long Zhu, Hui Guo and Jun Su
Nuclear Science and Techniques 34 (2) (2023)
https://doi.org/10.1007/s41365-023-01176-5

Colloquium : Machine learning in nuclear physics

Amber Boehnlein, Markus Diefenthaler, Nobuo Sato, Malachi Schram, Veronique Ziegler, Cristiano Fanelli, Morten Hjorth-Jensen, Tanja Horn, Michelle P. Kuchera, Dean Lee, Witold Nazarewicz, Peter Ostroumov, Kostas Orginos, Alan Poon, Xin-Nian Wang, Alexander Scheinker, Michael S. Smith and Long-Gang Pang
Reviews of Modern Physics 94 (3) (2022)
https://doi.org/10.1103/RevModPhys.94.031003

Prediction of neutron-induced fission product yields by a straightforward k -nearest-neighbor algorithm

Liang Tong, Ruonan He and Shiwei Yan
Physical Review C 104 (6) (2021)
https://doi.org/10.1103/PhysRevC.104.064617