Updates from Overleaf

slides/information-theory/slides-info-mutual-info2.tex

@@ -182,17 +182,19 @@
 
 \begin{vbframe} {Mutual information vs. correlation}
 
-  \begin{itemize}
+\begin{itemize}
     \item If two variables are independent, their correlation is 0.
     \item However, the reverse is not necessarily true. It is possible for two dependent variables to have 0 correlation because correlation only measures linear dependence.
+\end{itemize}
 
 \begin{center}
-\includegraphics[width = 10cm ]{figure/correlation_plot.png} \\
+\includegraphics[width = 0.99\textwidth]{figure/correlation_plot.png} \\
 \end{center}
 
+\begin{itemize}
     \item The figure above shows various scatterplots where, in each case, the correlation is 0 even though the two variables are strongly dependent, and MI is large. 
     \item Mutual information can therefore be seen as a more general measure of dependence between variables than correlation.
-  \end{itemize}
+\end{itemize}
 
 \end{vbframe}