Zobrazeno 1 - 10
of 4 062
pro vyhledávání: '"bayesian monte carlo"'
Autor:
Del Piccolo, Gianmarco, VanderBeek, Brandon P., Faccenda, Manuele, Morelli, Andrea, Byrnes, Joseph S.
Publikováno v:
Bulletin of the Seismological Society of America; Jun2024, Vol. 114 Issue 3, p1214-1226, 13p
Autor:
THANH BUI DAN1 thanhbd@hub.edu.vn, NGUYEN NGOC THACH2 thachnn@hub.edu.vn
Publikováno v:
Montenegrin Journal of Economics. Apr2024, Vol. 20 Issue 2, p251-265. 15p.
The final orbital configuration of a planetary system is shaped by both its early star-disk environment and late-stage gravitational interactions. Assessing the relative importance of each of these factors is not straightforward due to the observed d
Externí odkaz:
http://arxiv.org/abs/2207.07617
Autor:
Sugimoto, Saeki1 (AUTHOR), Takakura, Yuya1 (AUTHOR), Kajiro, Hiroshi2 (AUTHOR), Fujiki, Junpei1 (AUTHOR), Dashti, Hossein1 (AUTHOR), Yajima, Tomoyuki1 (AUTHOR), Kawajiri, Yoshiaki1 (AUTHOR) kawajiri@nagoya-u.jp
Publikováno v:
Journal of Advanced Manufacturing & Processing. Oct2023, Vol. 5 Issue 4, p1-17. 17p.
Publikováno v:
Phys. Rev. D 104, 074031 (2021)
We perform a global QCD analysis of unpolarized parton distributions within a Bayesian Monte Carlo framework, including the new $W$-lepton production data from the STAR Collaboration at RHIC and Drell-Yan di-muon data from the SeaQuest experiment at
Externí odkaz:
http://arxiv.org/abs/2109.00677
Publikováno v:
In Journal of Hydrology July 2023 622 Part A
Akademický článek
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Publikováno v:
Acoustics Australia. Mar2023, Vol. 51 Issue 1, p23-38. 16p.
Autor:
Acerbi, Luigi
Variational Bayesian Monte Carlo (VBMC) is a recently introduced framework that uses Gaussian process surrogates to perform approximate Bayesian inference in models with black-box, non-cheap likelihoods. In this work, we extend VBMC to deal with nois
Externí odkaz:
http://arxiv.org/abs/2006.08655
Autor:
Alhassan, E., Rochman, D., Vasiliev, A., Wohlmuther, M., Hursin, M., Koning, A. J., Ferroukhi, H.
In this work, we explore the use of an iterative Bayesian Monte Carlo (IBM) procedure for nuclear data evaluation within a Talys Evaluated Nuclear data Library (TENDL) framework. In order to identify the model and parameter combinations that reproduc
Externí odkaz:
http://arxiv.org/abs/2003.10827