\begin{frame}{Challenge Submission}
\framesubtitle{Backup}
    \begin{itemize}
        \item ECG-DualNet XL utilized
        \item Pre-training on Icentia$11\si{\kilo}$
        \item Optimized training ($8000$ samples) and validation ($528$ samples) split used
    \end{itemize}
    \begin{table}[!ht]
        \centering
        \caption{Classification results of ECG-DualNet XL pre-trained on the Icentia$11$k dataset and fine-tuned on the PhysioNet dataset with optimized submission split. Metric computed on the small validation set. Four class results on the top and two class results below.}
        \input{table/results_challenge}
        \label{tab:results_challenge}
    \end{table}
    \begin{center}
        \hspace{-0.15cm}\input{table/results_challenge_two_class}
    \end{center}
\end{frame}

\begin{frame}{Deep Double Decent}
\framesubtitle{Backup}
    \begin{figure}[!ht]
        \centering
        \vspace{-0.2cm}
        \includegraphics[width=0.6\textwidth]{artwork/deep_double_decent.png}
        \vspace{-0.2cm}
        \caption{Illustration of the deep double decent phenomenon in image classification (CIFAR-10 \& 15\% label noise). Image taken from \cite{Nakkiran2020}.}
        \label{fig:ddd}
    \end{figure}
\end{frame}