summaryrefslogtreecommitdiff
path: root/graphics/pgf/contrib/tikz-bayesnet/example.tex
diff options
context:
space:
mode:
authorNorbert Preining <norbert@preining.info>2019-09-02 13:46:59 +0900
committerNorbert Preining <norbert@preining.info>2019-09-02 13:46:59 +0900
commite0c6872cf40896c7be36b11dcc744620f10adf1d (patch)
tree60335e10d2f4354b0674ec22d7b53f0f8abee672 /graphics/pgf/contrib/tikz-bayesnet/example.tex
Initial commit
Diffstat (limited to 'graphics/pgf/contrib/tikz-bayesnet/example.tex')
-rw-r--r--graphics/pgf/contrib/tikz-bayesnet/example.tex158
1 files changed, 158 insertions, 0 deletions
diff --git a/graphics/pgf/contrib/tikz-bayesnet/example.tex b/graphics/pgf/contrib/tikz-bayesnet/example.tex
new file mode 100644
index 0000000000..19381bd8a1
--- /dev/null
+++ b/graphics/pgf/contrib/tikz-bayesnet/example.tex
@@ -0,0 +1,158 @@
+% example.tex
+%
+% Copyright (C) 2010,2011 Laura Dietz
+% Copyright (C) 2012 Jaakko Luttinen
+%
+% This file may be distributed and/or modified
+%
+% 1. under the LaTeX Project Public License and/or
+% 2. under the GNU General Public License.
+%
+% See the files LICENSE_LPPL and LICENSE_GPL for more details.
+
+\documentclass[a4paper]{article}
+
+\usepackage{tikz}
+\usetikzlibrary{bayesnet}
+%\pgfrealjobname{example} % name of this file
+
+\title{Graphical Models in Tikz}
+\author{Laura Dietz, Jaakko Luttinen}
+
+\begin{document}
+
+\maketitle
+
+TikZ examples for graphical models (Bayesian networks) and directed
+factor graphs \cite{Dietz:2010}.
+
+% A table of node types
+\begin{table}[ht]
+ \caption{Node types}
+ \begin{center}
+ \begin{tabular}{llc}
+ Type & Syntax & Output
+ \\
+ \hline
+ Latent variable &
+ \texttt{\textbackslash node[latent]} &
+ \tikz{ %
+ \node[latent] {$x$}; %
+ }
+ \\
+ Observed variable &
+ \texttt{\textbackslash node[obs]} &
+ \tikz{ %
+ \node[obs] {$y$}; %
+ }
+ \\
+ Deterministic &
+ \texttt{\textbackslash node[det]} &
+ \tikz{ %
+ \node[det] {dot} ; %
+ }
+ \\
+ Constant &
+ \texttt{\textbackslash node[const]} &
+ \tikz{ %
+ \node[const] {$a$}; %
+ }
+ \\
+ Factor &
+ \texttt{\textbackslash node[factor]} &
+ \tikz{ %
+ \node[factor] [label=$\mathcal{N}$] {}; %
+ }
+ \\
+ Factor with nodes &
+ &
+ \tikz{ %
+ \node[obs] (y) {$y$} ; %
+ \node[latent, left=of y, yshift=0.5cm] (mu) {$\mu$} ; %
+ \node[latent, left=of y, yshift=-0.5cm] (tau) {$\tau$} ; %
+ \factor[left=of y] {y-factor} {$\mathcal{N}$} {} {};
+ \factoredge {mu,tau} {y-factor} {y} ; %
+ }
+ \\
+ Plate &
+ \texttt{\textbackslash plate} &
+ \tikz{ %
+ \node[latent] (x) {$x_m$}; %
+ \plate {} {(x)} {$m \in \mathcal{M}$}; %
+ }
+ \\
+ Gate &
+ &
+ \tikz{
+ % Nodes
+ \node[obs] (k) {$k$}; %
+ \node[latent, above=2 of k] (l) {$\lambda$}; %
+ \factor[above=0.8 of k] {k-f} {Multi} {} {}; %
+ \node[latent, right=of k-f] (paa) {$\phi$}; %
+ %\node[latent, right=of k-f] (p) {$\phi$}; %
+ % Connections
+ \factoredge {paa} {k-f} {k} ; %
+ % Gate
+ \gate {} {(k-f)(k-f-caption)} {l} ; %
+ }
+ \end{tabular}
+ \end{center}
+\end{table}
+
+
+% Simple Bayesian network
+\begin{figure}[ht]
+ \begin{center}
+ \begin{tabular}{cc}
+ \input{model_pca} &
+ \input{model_pca2}
+ \end{tabular}
+ \end{center}
+ \caption{PCA model as a Bayesian network and a directed factor
+ graph.}
+\end{figure}
+
+% Latent Dirichlet allocation
+\begin{figure}[ht]
+ \begin{center}
+ \input{model_lda}
+ \end{center}
+ \caption{Latent Dirichlet allocation as directed factor graph.}
+\end{figure}
+
+% Citation influence model
+\begin{figure}[ht]
+ \begin{center}
+ \input{model_citation_influence}
+ \end{center}
+ \caption{Citation influence model with own topics \cite{Dietz:2007}
+ as directed factor graph.}
+\end{figure}
+
+\clearpage
+
+\begin{thebibliography}{9}
+
+\bibitem{Dietz:2010}
+ Laura Dietz,
+ \emph{Directed Factor Graph Notation for Generative Models}.
+ Technical Report. 2010
+
+% Laura Dietz, Steffen Bickel, Tobias Scheffer.
+% Unsupervised Prediction of Citation Influences.
+% In: Proceedings of International Conference on Machine Learning. 2007
+\bibitem{Dietz:2007}
+ Laura Dietz, Steffen Bickel, Tobias Scheffer,
+ \emph{Unsupervised Prediction of Citation Influences}.
+ In: Proceedings of International Conference on Machine
+ Learning. 2007
+
+
+\end{thebibliography}
+
+\end{document}
+
+%%% Local Variables:
+%%% mode: tex-pdf
+%%% TeX-master: t
+%%% End: