39 lines
1.4 KiB
TeX
39 lines
1.4 KiB
TeX
\begin{frame}
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\frametitle{Topic 1: Shapley Values}
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%\Large \\
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\LARGE \textbf{Chapter:} 9.2,9.5 and 9.6 + 2/3 papers \\
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\textbf{Supervisor:} Chiara Balestra (chiara.balestra@cs.uni-dortmund.de)\\
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%\begin{center}
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%\includegraphics[height=3cm]{illustrations/chiara.png}
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%\end{center}
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\begin{columns}
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%\begin{column}{.3\textwidth}
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% \begin{center}
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% \includegraphics[height=3cm]{illustrations/chiara.png}
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% \end{center}
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%\end{column}
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\begin{column}{0.475\textwidth}
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Focus either on Computer Science
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\begin{itemize}
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\item \small\textbf{Shapley Values for Feature Selection: The Good, the Bad, and the Axioms} (Fryer et al. 2020)
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\item \textbf{Explaining Models by Propagating Shapley Values of Local Components} (Chen et al. 2020)
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\item \textbf{GraphSVX: Shapley Value Explanations for Graph Neural Networks} (Duval et al. 2021)
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\end{itemize}
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\end{column}
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\begin{column}{0.475\textwidth}
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Or on Medical Application
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\begin{itemize}
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\item \small\textbf{Identifying mortality factors from Machine Learning using Shapley values – a case of COVID19} (Smith et al. 2021)
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\item \textbf{Explaining multivariate molecular diagnostic tests via Shapley values} (Roder et al. 2021)
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\end{itemize}
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\end{column}
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\end{columns}
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\end{frame}
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