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Title: Refining mass formulas for astrophysical applications: A Bayesian neural network approach

Authors:
;
Publication Date:
Sponsoring Org.:
USDOE
OSTI Identifier:
1398291
Grant/Contract Number:  
FG02-92ER40750
Resource Type:
Journal Article: Publisher's Accepted Manuscript
Journal Name:
Physical Review C
Additional Journal Information:
Journal Name: Physical Review C Journal Volume: 96 Journal Issue: 4; Journal ID: ISSN 2469-9985
Publisher:
American Physical Society
Country of Publication:
United States
Language:
English

Citation Formats

Utama, R., and Piekarewicz, J.. Refining mass formulas for astrophysical applications: A Bayesian neural network approach. United States: N. p., 2017. Web. doi:10.1103/PhysRevC.96.044308.
Utama, R., & Piekarewicz, J.. Refining mass formulas for astrophysical applications: A Bayesian neural network approach. United States. doi:10.1103/PhysRevC.96.044308.
Utama, R., and Piekarewicz, J.. Fri . "Refining mass formulas for astrophysical applications: A Bayesian neural network approach". United States. doi:10.1103/PhysRevC.96.044308.
@article{osti_1398291,
title = {Refining mass formulas for astrophysical applications: A Bayesian neural network approach},
author = {Utama, R. and Piekarewicz, J.},
abstractNote = {},
doi = {10.1103/PhysRevC.96.044308},
journal = {Physical Review C},
number = 4,
volume = 96,
place = {United States},
year = {Fri Oct 06 00:00:00 EDT 2017},
month = {Fri Oct 06 00:00:00 EDT 2017}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record at 10.1103/PhysRevC.96.044308

Citation Metrics:
Cited by: 4 works
Citation information provided by
Web of Science

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Works referenced in this record:

Nuclear Ground-State Masses and Deformations
journal, March 1995

  • Moller, P.; Nix, J. R.; Myers, W. D.
  • Atomic Data and Nuclear Data Tables, Vol. 59, Issue 2, p. 185-381
  • DOI: 10.1006/adnd.1995.1002