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\documentclass[12pt,a4paper,twoside]{report}
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\input{macros}
\input{cmds}
\title{VEIN: VErification via Interaction Nets for Neural Networks}
\author{Eric Marin}
\date{\today}
\begin{document}
\maketitle
\begin{abstract}
This thesis introduces \textbf{VEIN} (VErification via Interaction Nets), a framework for neural network
verification with a focus on neural network equivalence. It acts as a formally verified
preprocessor that reduces neural networks to a normal form before they can be compared by a solver.
To enable this reduction, \textbf{VEIN} translates neural networks into Interaction Nets, a graph rewriting
computational model, and applies a set of graph rewriting rules to reduce the network into an
Abstract Syntax Tree. We present the complete framework and provide in detail: the translation
process, the graph rewriting rules and rigorous proofs of both soundness and termination for the
reduction process.
\end{abstract}
\tableofcontents
% Introduction: Context -> Problem -> Solution -> Validation -> Outline
\input{chapters/01-introduction}
% Background
\input{chapters/02-background}
% Core
\input{chapters/03-core}
% Related Work
\input{chapters/04-related-work}
% Conclusion
\input{chapters/05-conclusion}
\bibliographystyle{plain}
\bibliography{references}
\end{document}
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