Uncertainty quantification in nuclear criticality modelling using methods of polynomial chaos

Autor: Ayres, Daniel

In this thesis we use polynomial chaos expansions to represent the response of criticality calculations when they are subject to large numbers (many hundreds) of correlated nuclear data uncertainties. An adaptive high dimensional model representation

Externí odkaz: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.668241

BEAGLE 3 : Improved Performance, Scaling, and Usability for a High-Performance Computing Library for Statistical Phylogenetics

Autor: Ayres, Daniel L., Cummings, Michael P., Baele, Guy, Darling, Aaron E., Lewis, Paul O., Swofford, David L., Huelsenbeck, John P., Lemey, Philippe, Rambaut, Andrew, Suchard, Marc A.

Publikováno v: Systematic Biology, 2019 Nov 01. 68(6), 1052-1061.

Externí odkaz: https://www.jstor.org/stable/26842021

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MrBayes 3.2: Efficient Bayesian Phylogenetic Inference and Model Choice Across a Large Model Space

Autor: Ronquist, Fredrik, Teslenko, Maxim, van der Mark, Paul, Ayres, Daniel L., Darling, Aaron, Höhna, Sebastian, Larget, Bret, Liu, Liang, Suchard, Marc A., Huelsenbeck, John P.

Publikováno v: Systematic Biology, 2012 May 01. 61(3), 539-542.

Externí odkaz: https://www.jstor.org/stable/41515220

BEAGLE 3 high-performance computational library for phylogenetic inference

Autor: Ayres, Daniel, Lemey, Philippe, Baele, Guy, Suchard, Marc A

Publikováno v: Phylogenetics in the Genomic Era
Scornavacca, Celine; Delsuc, Frédéric; Galtier, Nicolas. Phylogenetics in the Genomic Era, No commercial publisher | Authors open access book, pp.5.4:1--5.4:9, 2020

International audience; Maximum-likelihood and Bayesian inference approaches to statistical phylogenetics require repeatedly computing of the observed sequence data likelihood. As increasingly cheaper sequencing technology provides phylogenomic studi

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::c0a75a923bedc691a77e12f373a917b8
https://lirias.kuleuven.be/handle/123456789/665906