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pro vyhledávání: '"Beschle, Cedric"'
Autor:
Beschle, Cedric Aaron, Barth, Andrea
Continuous level Monte Carlo is an unbiased, continuous version of the celebrated multilevel Monte Carlo method. The approximation level is assumed to be continuous resulting in a stochastic process describing the quantity of interest. Continuous lev
Externí odkaz:
http://arxiv.org/abs/2305.15949
Autor:
Beschle, Cedric Aaron, Barth, Andrea
This paper provides a framework in which multilevel Monte Carlo and continuous level Monte Carlo can be compared. In continuous level Monte Carlo the level of refinement is determined by an exponentially distributed random variable, which therefore h
Externí odkaz:
http://arxiv.org/abs/2303.08694
Autor:
Beschle, Cedric Aaron, Kovács, Balázs
In this paper, we consider a non-linear fourth-order evolution equation of Cahn-Hilliard-type on evolving surfaces with prescribed velocity, where the non-linear terms are only assumed to have locally Lipschitz derivatives. High-order evolving surfac
Externí odkaz:
http://arxiv.org/abs/2006.02274
Autor:
Beschle, Cedric Aaron, Barth, Andrea
Continuous level Monte Carlo is an unbiased, continuous version of the celebrated multilevel Monte Carlo method. The approximation level is assumed to be continuous resulting in a stochastic process describing the quantity of interest. Continuous lev
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e78c586493a335dd9063584acb48ccd9
http://arxiv.org/abs/2305.15949
http://arxiv.org/abs/2305.15949
Akademický článek
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Autor:
Hägele, David, Schulz, Christoph, Beschle, Cedric, Booth, Hannah, Butt, Miriam, Barth, Andrea, Deussen, Oliver, Weiskopf, Daniel
Publikováno v:
IT: Information Technology; Aug2022, Vol. 64 Issue 4/5, p121-132, 12p