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\usepackage{graphicx}
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\usepackage{booktabs} % for professional tables
\usepackage{xspace}
\usepackage{amsmath}
\usepackage{placeins}
\usepackage{todonotes}
\usepackage{wrapfig}
\usepackage{hyperref}
\usepackage[title]{appendix}
\input{mydef.tex}

\usepackage{marvosym} 
\usepackage{footnote}

\usepackage[final]{neurips_2023}
%\usepackage{neurips_2023}
\title{Direct Training of SNN using Local Zeroth Order Method}

\author{%
  Bhaskar Mukhoty$^{1,}$\thanks{First co-author}
  \And
   Velibor Bojkovi\'c$^{1,*}$ 
    \And
   William de Vazelhes$^1$
   \And
   Xiaohan Zhao$^3$
   \And
   Giulia De Masi$^{2,6}$
   \And
   Huan Xiong$^{1,5,}$\thanks{Correspondence to Huan Xiong (huan.xiong.math@gmail.com), and Bin Gu
(jsgubin@gmail.com).}
   \And
   Bin Gu$^{1,4,\dagger}$%\thanks{Corresponding Author:}
   \And\\
    $^1$ Mohamed bin Zayed University of Artificial Intelligence, UAE\\
    $^2$ ARRC, Technology Innovation Institute, UAE \\
     $^2$ Nanjing University of Information Science and Technology, China\\
   $^4$ School of Artificial Intelligence, Jilin University, China \\
 $^5$ Harbin Institute of Technology, China\\
$^6$ BioRobotics Institute, Sant’Anna School of Advanced Studies, Pisa, Italy
}


%\usepackage[13-20]{pagesel}
\begin{document}

\maketitle

\input{main}
\bibliography{robustness}
\bibliographystyle{plain}
\clearpage

\begin{appendices}
\begin{center}
\textbf{\large Appendix: Direct Training of SNN using Local Zeroth Order Method }
\end{center}
\input{app}
\end{appendices}

\end{document}

