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authorThibaut Horel <thibaut.horel@gmail.com>2015-12-12 00:28:23 -0500
committerThibaut Horel <thibaut.horel@gmail.com>2015-12-12 00:28:23 -0500
commit6f876aa0fa8596eec71eec640ca9556b48034b6f (patch)
tree20e8c339802978a7e2f564704e2a75888c3dd05a /finale/sections/appendix.tex
parentc760d533c1a44f98b2f660f64ea8354a7f896121 (diff)
downloadcascades-6f876aa0fa8596eec71eec640ca9556b48034b6f.tar.gz
Abandonned by my project partner... finishing up experiment section
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+\begin{figure*}
+\centering
+\subfigure[][50 cascades]{
+\includegraphics[scale=.4]{../simulation/plots/2015-11-05_22:52:30.pdf}}\hspace{1em}%
+\subfigure[][100 cascades]{
+\includegraphics[scale=.4]{../simulation/plots/2015-11-05_22:52:47.pdf}}\\
+\subfigure[][150 cascades]{
+\includegraphics[scale=.4]{../simulation/plots/2015-11-05_22:53:24.pdf}}\hspace{1em}%
+\subfigure[][200 cascades]{
+\includegraphics[scale=.4]{../simulation/plots/2015-11-05_22:55:39.pdf}}\\
+\subfigure[][250 cascades]{
+\includegraphics[scale=.4]{../simulation/plots/2015-11-05_22:57:26.pdf}}\hspace{1em}%
+\subfigure[][1000 cascades]{
+\includegraphics[scale=.4]{../simulation/plots/2015-11-05_22:58:29.pdf}}
+\caption{Bayesian Inference of $\Theta$ with MCMC using a $Beta(1, 1)$ prior on
+each edge. For each figure, the plot $(i, j)$ on the $i^{th}$ row and $j^{th}$
+column represent a histogram of samples taken from the posterior of the
+corresponding edge $\Theta_{i, j}$. The red line indicates the true value of the
+edge weight. If an edge does not exist (has weight $0$) the red line is
+confounded with the y axis.}
+\label{betapriorbayeslearning}
+\end{figure*}