Erwin Alhassan; Dimitri Rochman; Alexander Vasiliev; Mathieu Hursin; Arjan J. Koning; Hakim Ferroukhi

doi:10.1007/s41365-022-01034-w

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Iterative Bayesian Monte Carlo for nuclear data evaluation

NUCLEAR PHYSICS AND INTERDISCIPLINARY RESEARCH | Updated：2022-12-16

- Iterative Bayesian Monte Carlo for nuclear data evaluation Cover Article Enhanced Publication
- Nuclear Science and Techniques Vol.33, Issue 4, (2022)
- Affiliations：
  
  Laboratory for Reactor Physics and Thermal-Hydraulics, Paul Scherrer Institute,Villigen,Switzerland,5232;Division Large Research Facilities (GFA), Paul Scherrer Institute,Villigen,Switzerland;École Polytechnique Fédérale de Lausanne,Lausanne,Switzerland;Nuclear Data Section, International Atomic Energy Commission (IAEA),Vienna,Austria;Division of Applied Nuclear Physics, Department of Physics and Astronomy, Uppsala University,Uppsala,Sweden
- Author bio：
- Funds：
- DOI：10.1007/s41365-022-01034-w CLC：
- Published：2022-04，
  
  Published Online：01 May 2022，
  
  Received：03 December 2021，
  
  Revised：21 February 2022，
  
  Accepted：12 March 2022
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Cite this article
Erwin Alhassan, Dimitri Rochman, Alexander Vasiliev, et al. Iterative Bayesian Monte Carlo for nuclear data evaluation. [J]. Nuclear Science and Techniques 33(4):50(2022)
DOI：

Erwin Alhassan, Dimitri Rochman, Alexander Vasiliev, et al. Iterative Bayesian Monte Carlo for nuclear data evaluation. [J]. Nuclear Science and Techniques 33(4):50(2022) DOI： 10.1007/s41365-022-01034-w.

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Iterative Bayesian Monte Carlo for nuclear data evaluation Cover Article Enhanced Publication