dl_latex_collection.tex

% A collection of PGF/TikZ figures for Deep Learning,
% using a decompossed method to illustrate.
% Written by Ling KangJie<1815428489@qq.com>

% Reference: https://github.com/PetarV-/TikZ 
\documentclass{article}
\usepackage[margin=12mm]{geometry}
\usepackage{hyperref}
\usepackage{tikz}
\usepackage{amsmath}
\usepackage{tikz}
\usepackage{amsmath}
\usepackage{amssymb}
\usepackage{etoolbox}
\usepackage{xcolor}
\usepackage{amssymb}
\usepackage{xcolor}
\usepackage{pgfplots}
\usepackage{braids}
\usepackage{etoolbox}
\usepackage{tkz-graph}
\usepackage{pgfplots}
\usepackage{amsbsy}
\usepackage{etoolbox}

\usetikzlibrary{arrows,decorations.pathmorphing,backgrounds,positioning,fit,petri, decorations.pathreplacing,shadows,calc}
\usetikzlibrary{automata, chains, decorations.pathmorphing, positioning}
\usepackage{relsize}
\usetikzlibrary{automata, patterns,positioning}
\usepackage{bm}

\usepackage{tkz-graph}
\usetikzlibrary{snakes}

\usetikzlibrary{arrows,backgrounds}
\usetikzlibrary{positioning, decorations.pathmorphing, shapes}
\usetikzlibrary{matrix}
\usetikzlibrary{calc}


\definecolor{olivegreen}{rgb}{0,0.6,0}

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\usepackage{listings}
\usepackage{color}
\definecolor{listinggray}{gray}{0.92}
\lstset{ %
language=[LaTeX]TeX,
breaklines=true,
frame=single,
basicstyle=\footnotesize\ttfamily,
backgroundcolor=\color{listinggray},
keywordstyle=\color{blue}
}
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\hypersetup{
  colorlinks=true,
  linkcolor=blue,
  anchorcolor=black,
  citecolor=olive,
  filecolor=magenta,
  menucolor=red,
  urlcolor=blue
}
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\newcommand{\demo}[2][1]{
\begin{minipage}{.49\linewidth}
\centering
\resizebox{#1\linewidth}{!}{
\input{demo/#2}
}
\end{minipage}
\hspace{0.01\linewidth}
\begin{minipage}{0.5\linewidth}
\lstinputlisting{demo/#2}
\end{minipage}
}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\newcommand{\example}[1]{
\resizebox{\linewidth}{!}{
\input{demo/#1}
}
\lstinputlisting{demo/#1}
}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 

\begin{document}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\title{A Collection of PGF/TikZ Examples for Deep Learning}
\author{\href{1815428489@qq.com}{Ling KangJie}}
\date{\today{}~(v0.1.0)}
\maketitle
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

\begin{abstract}
  This document is a collection of common examples for scientific papers particularly for Deep Learning topics by using PGF/TikZ package.
Reference: 
  \href{https://github.com/PetarV-/TikZ}{https://github.com/PetarV-/TikZ}.
\end{abstract}

\tableofcontents

\section{Deep Learning}

\subsection{2D Convolution Operation}
\example{2d_convolution}
\subsection{A3C execution}
\example{a3c_execution}
\subsection{A3C Neural Network}
\example{a3c_neural_network}
\subsection{Amplitude Modulation}
\example{amplitude_modulation}
\subsection{A Trous Convolutions}
\example{a_trous_convolutions}
\subsection{Bidirectional Long Short Term Memory}
\example{bidirectional_long_short-term_memory}
\subsection{BWT}
\example{bwt}
\subsection{Convolutional Autoencoder}
\example{convolutional_autoencoder}
\subsection{Convolutional Cross-connection}
\example{convolutional_cross-connection}

\subsection{Coordinate Systems}
\example{coordinate_systems}
\subsection{CRT Rendering}
\example{crt_rendering}
\subsection{Cyclegan}
\example{cyclegan}
\subsection{Deep Belif Network}
\example{deep_belief_network}
\subsection{Deep Graph Infomax}
\example{deep_graph_infomax}
\subsection{de-bruijn-graph}
\example{de_bruijn_graph}

\subsection{DNA}
\example{dna}
\subsection{Dropout}
\example{dropout}
\subsection{Emulator Modules}
\example{emulator_modules}
\subsection{Fetch Decode Execute cycle}
\example{fetch-decode-execute_cycle}

\subsection{Frequence Modulation}
\example{frequency_modulation}
\subsection{Fully Connected Cross Connection}
\example{fully-connected_cross-connection}
\subsection{GameBoy Joypad Register}
\example{gameboy_joypad_register}
\subsection{Gameboy Palette Translation}
\example{gameboy_palette_translation}
\subsection{Gameboy Tiling System}
\example{gameboy_tiling_system}

\subsection{Gat Layer}
\example{gat_layer}
\subsection{Generative Adversarial Network}
\example{generative_adversarial_network}
\subsection{Gene Expression}
\example{gene_expression}
\subsection{Git Dataflow}
\example{git_dataflow}
\subsection{Git WorkFlow}
\example{git_workflow}
\subsection{Gamhmm}
\example{gmhmm}
\subsection{Graph Convolution}
\example{graph_convolution}
\subsection{Hamitonian Graph}
\example{hamiltonian_graph}
\subsection{Hierachical Graph Classifier}
\example{hierarchical_graph_classifier}

\subsection{Hmm Transition Smoothing}
\example{hmm_transition_smoothing}
\subsection{Insruction Execution}
\example{instruction_execution}
\subsection{IQ Sampling}
\example{iq_sampling}
\subsection{Lego Deep Learning}
\example{lego_deep_learning}
\subsection{Long Short Term Memory}
\example{long_short-term_memory}
\subsection{Maximum Flow Problem}
\example{maximum_flow_problem}
\subsection{MCL}
\example{mcl}
\subsection{Message Passing Neural Network}
\example{message_passing_neural_network}
\subsection{Multilayer Network}
\example{multilayer_network}

\subsection{Multilayer Perceptron}
\example{multilayer_perceptron}
\subsection{Multiplex Chain Gmhmm}
\example{multiplex_chain_gmhmm}
\subsection{Multiplex Chain Gmhmm Beta}
\example{multiplex_chain_gmhmm_beta}
\subsection{Multiplex Epidemic Awareness Network}
\example{multiplex_epidemics-awareness_network}
\subsection{Multiplex Network Underlying Graph}
\example{multiplex_network_underlying_graph}
\subsection{Muxstep Pipeline}
\example{muxstep_pipeline}
\subsection{Progressive Alignment}
\example{progressive_alignment}
\subsection{Progressive Neural Network}
\example{progressive_neural_network}
\subsection{Reinforcement Learning Greedy Policy}
\example{reinforcement_learning_greedy_policy}
\subsection{Relational Network}
\example{relational_network}
\subsection{RN Object Extraction}
\example{rn_object_extraction}
\subsection{Sampling}
\example{sampling}

\subsection{Self-attention}
\example{self-attention}
\subsection{Semi-supervised Embedding}
\example{semi-supervised_embedding}
\subsection{Semi-supervised Learning}
\example{semi-supervised_learning}
\subsection{Shortest Path Problem}
\example{shortest_path_problem}
\subsection{Sparse DGI}
\example{sparse_dgi}
\subsection{Supervised Learning Setup}
\example{supervised_learning_setup}
\subsection{Variational Denoising Autoencoder}
\example{variational_denoising_autoencoder}
\subsection{Web Graph}
\example{web_graph}
\subsection{X-CNN}
\example{x-cnn}
\subsection{X-LSTM}
\example{x-lstm}

\end{document}