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\frametitle{Topic 4: Shapley Values}

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	\LARGE \textbf{Chapter:} 9.2,9.5 and 9.6 + 2/3 papers \\
	\textbf{Supervisor:} Chiara Balestra (chiara.balestra@cs.uni-dortmund.de)\\

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            \begin{itemize}
                \item Use game theory to explain the output of a model
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                    \item on cs theory 
                    \begin{itemize}
                        \item \textbf{Shapley Values for Feature Selection: The Good, the Bad, and the Axioms} (Fryer et al. 2020)
                        \item \textbf{Explaining Models by Propagating Shapley Values of Local Components} (Chen et al. 2020)
                        \item \textbf{GraphSVX: Shapley Value Explanations for Graph Neural Networks} (Duval et al. 2021)
                    \end{itemize}
                    \item on medical application
                    \begin{itemize}
                        \item \textbf{Identifying mortality factors from Machine Learning using Shapley values – a case of COVID19} (Smith et al. 2021)
                        \item \textbf{Explaining multivariate molecular diagnostic tests via Shapley values} (Roder et al. 2021)
                    \end{itemize} 
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