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kumar-shridhar committed Dec 4, 2018
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14 changes: 8 additions & 6 deletions Appendix1/appendix1.tex
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Expand Up @@ -6,7 +6,7 @@ \section*{Bayesian Settings}

\subsection{Image Recognition}

\begin{table}[h!]
\begin{table}[H]
\centering
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\begin{tabular}[c]{c | c}
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\end{table}

Sample size can vary from 10 to 25 as this range provided the best results. However, it can be played around with. For most of our experiments it is either 10 or 25 unless specified otherwise.
Sample size can vary from 10 to 25 as this range provided the best results. However, it can be played around with. For most of our experiments, it is either 10 or 25 unless specified otherwise.

\subsection{Image Super Resolution}

\begin{table}[h!]
\begin{table}[H]
\centering
\renewcommand{\arraystretch}{2}
\begin{tabular}[c]{c | c}
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\subsection{Generative Adversarial Network}

\begin{table}[h!]
\begin{table}[H]
\centering
\renewcommand{\arraystretch}{2}
\begin{tabular}[c]{c | c}
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\subsection{Image Recognition}

\begin{table}[h!]
\begin{table}[H]
\centering
\renewcommand{\arraystretch}{2}
\begin{tabular}[c]{c | c}
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\renewcommand{\arraystretch}{2}
\end{table}

The weights were initialized with Xavier initialization \cite{glorot2010understanding} at first, but to make it consistent with the Bayesian networks where initialization was Normal initialization (mean = 0 and variance = 1), the initiliazer was changed to Normal initialization.
The weights were initialized with Xavier initialization \cite{glorot2010understanding} at first, but to make it consistent with the Bayesian networks where initialization was Normal initialization (mean = 0 and variance = 1), the initializer was changed to Normal initialization.

\pagebreak

\section*{Architectures}

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