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Mpp
MLUQ
Commits
e3a06357
Commit
e3a06357
authored
Sep 03, 2020
by
niklas.baumgarten
Browse files
added abstract and title image
parent
b0e038ec
Changes
4
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tex/logos/titleimage_wp_slides.png
0 → 100644
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e3a06357
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tex/out/slides.pdf
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tex/slides.tex
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e3a06357
\documentclass
[18pt]
{
beamer
}
\usepackage
{
defs
}
\usepackage
{
templates/beamerthemekit
}
\titleimage
{
titleimage
_
wp
_
slides.png
}
\title
{
Multilevel Monte Carlo Applications
}
\subtitle
{
Review of implementation and results
}
...
...
@@ -12,6 +13,8 @@
\titlepage
\end{frame}
\input
{
src/abstract
}
\begin{frame}
{
Outline
}
\tableofcontents
\end{frame}
...
...
@@ -31,8 +34,8 @@
% \input{src/outlook}
\begin{frame}
{
References
}
\bibliographystyle
{
acm
}
\tiny
{
\bibliography
{
lit
}}
%
\bibliographystyle{acm}
%
\tiny{\bibliography{lit}}
\end{frame}
\section*
{
Backup
}
...
...
tex/src/abstract.tex
0 → 100644
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e3a06357
\begin{frame}
{
Abstract
}
\textit
{
Multilevel Monte Carlo methods have gained much popularity in
recent years.
Their ability to estimate expectation values on high dimensional
probability spaces have made them the method of choice for computing
expected solutions of PDEs with random coefficients.
Furthermore, their non-intrusive implementation schemes have
allowed them to build on existing theory and software.
}
\vspace
{
0.2cm
}
\textit
{
In this talk, we present a short overview on the method, the used
heuristics and present our applications on elliptic, parabolic
and hyperbolic PDEs with different sources of randomness.
We want to finish the talk by presenting numerical results and
giving an outlook on further applications for wave propagation
and nonlinear parabolic PDEs.
}
\end{frame}
\ No newline at end of file
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