Issue
EPJ Nuclear Sci. Technol.
Volume 4, 2018
Special Issue on 4th International Workshop on Nuclear Data Covariances, October 2–6, 2017, Aix en Provence, France – CW2017
Article Number 33
Number of page(s) 10
Section Covariance Evaluation Methodology
DOI https://doi.org/10.1051/epjn/2018013
Published online 14 November 2018
  1. C.E. Rasmussen, C.K.I. Williams, Gaussian Processes for Machine Learning (MIT Press, Cambridge, Mass., 2006) [Google Scholar]
  2. D.W. Muir, A. Trkov, I. Kodeli, R. Capote, V. Zerkin, The Global Assessment of Nuclear Data, GANDR (EDP Sciences, 2007) [Google Scholar]
  3. H. Leeb, D. Neudecker, T. Srdinko, Nucl. Data Sheets 109, 2762 (2008) [CrossRef] [Google Scholar]
  4. M. Herman, M. Pigni, P. Oblozinsky, S. Mughabghab, C. Mattoon, R. Capote, Y.S. Cho, A. Trkov, Tech. Rep. BNL-81624-2008-C P, Brookhaven National Laboratory, 2008 [Google Scholar]
  5. J. Quiñonero-Candela, C.E. Rasmussen, J. Mach. Learn. Res. 6, 1939 (2005) [Google Scholar]
  6. E. Snelson, Z. Ghahramani, Sparse Gaussian Processes Using Pseudo-Inputs, in Advances in Neural Information Processing Systems (2006), pp. 1257–1264 [Google Scholar]
  7. D. Mancusi, A. Boudard, J. Cugnon, J.C. David, P. Kaitaniemi, S. Leray, New C++ Version of the Liège Intranuclear Cascade Model in Geant4 (EDP Sciences, 2014), p. 05209 [Google Scholar]
  8. D. Mancusi, A. Boudard, J. Cugnon, J.C. David, P. Kaitaniemi, S. Leray, Phys. Rev. C 90, 054602 (2014) [CrossRef] [Google Scholar]
  9. A. Kelic, M.V. Ricciardi, K. H. Schmidt (2009) [Google Scholar]
  10. N. Otuka, E. Dupont, V. Semkova, B. Pritychenko, A. Blokhin, M. Aikawa, S. Babykina, M. Bossant, G. Chen, S. Dunaeva et al., Nucl. Data Sheets 120, 272 (2014) [CrossRef] [Google Scholar]
  11. B.J.N. Blight, L. Ott, Biometrika 62, 79 (1975) [CrossRef] [Google Scholar]
  12. M.T. Pigni, H. Leeb, Uncertainty estimates of evaluated 56fe cross sections based on extensive modelling at energies beyond 20 MeV, in Proc. Int. Workshop on Nuclear Data for the Transmutation of Nuclear Waste. GSI-Darmstadt, Germany (2003) [Google Scholar]
  13. G. Schnabel, Ph.D. thesis, Technische Universität Wien, Vienna, 2015 [Google Scholar]
  14. G. Schnabel, H. Leeb, EPJ Web Conf. 111, 09001 (2016) [CrossRef] [Google Scholar]
  15. R.H. Byrd, P. Lu, J. Nocedal, C. Zhu, SIAM J. Sci. Comput. 16, 1190 (1995) [CrossRef] [MathSciNet] [Google Scholar]
  16. IAEA benchmark 2010, https://www-nds.iaea.org/spallations/ [Google Scholar]
  17. J.C. David, Eur. Phys. J. A 51, 68 (2015) [CrossRef] [EDP Sciences] [Google Scholar]
  18. MYRRHA: An innovative research installation, http://sckcen.be/en/Technology_future/MYRRHA [Google Scholar]
  19. R Development Core Team, R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, Vienna, Austria, 2008) [Google Scholar]
  20. W.B. Amian, R.C. Byrd, C.A. Goulding, M.M. Meier, G.L. Morgan, C.E. Moss, D.A. Clark, Nucl. Sci. Eng. 112, 78 (1992) [CrossRef] [Google Scholar]
  21. T. Nakamoto, K. Ishibashi, N. Matsufuji, N. Shigyo, K. Maehata, S.I. Meigo, H. Takada, S. Chiba, M. Numajiri, T. Nakamura et al., J. Nucl. Sci. Technol. 32, 827 (1995) [CrossRef] [Google Scholar]
  22. K. Ishibashi, H. Takada, T. Nakamoto, N. Shigyo, K. Maehata, N. Matsufuji, S.I. Meigo, S. Chiba, M. Numajiri, Y. Watanabe et al., J. Nucl. Sci. Technol. 34, 529 (1997) [CrossRef] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.