Attachment 'Context.tex'

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   1 %!TEX TS-program = pdflatex
   2 %!TEX encoding = Latin1
   3 %!TEX root = perrinet09int.tex
   4 \section{Introduction}%
   5 \frame{\titlepage}%
   6 %
   7 \begin{frame}\frametitle{Outline}%
   8 %----------------------------------------------------------------------------------------------------%
   9 \begin{itemize}%
  10     \item Context: coding of static natural images
  11 %    \item  toward coding of motion flows
  12     \item Decoding low-level neural information to track visual motion:
  13   	\begin{itemize}%
  14   		  \item Probabilistic representations
  15   		  \item General formulation for spatio-temporal integration
  16 		  \item Dynamical recurrent models of motion estimation
  17   	\end{itemize}%
  18     \end{itemize}%
  19 \end{frame}%
  20 \section{Context}%
  21 %: 1min 
  22 \begin{frame}\frametitle{Context: Coding of natural images}%
  23 \begin{columns}%
  24 	\begin{column}[c]{.66\textwidth}%
  25 		\includegraphics[width=\linewidth]{../Learning/08-11-24_NeuralComp_v1/figures/SparseSpikeCoding.pdf}%
  26 	\end{column}%
  27 	\begin{column}[c]{.28\textwidth}%
  28 		\includegraphics[width=\linewidth]{../../Motion/SpatialSummation/06-10_NeuroComp_talk/figures/perrinet-fischer.png}%
  29 	\end{column}%
  30 \end{columns}%
  31 %\\%
  32 \vspace*{1.2cm}%
  33 $\mathcal{C}(\mathbf{s} |\mathbf{x}, \mathbf{A} ) =   \frac{1}{2.\sigma^2}.\|  \mathbf{x} - \sum_j s_j . \mathbf{A}_j \|^2 + \log_2(M) .  \| \mathbf{s} \|_0  $%
  34 \end{frame}%
  35 %: 2min 
  36 \begin{frame}\frametitle{Context: Coding of natural images}%
  37 \includemovie[%
  38 poster,%
  39 controls%,loop
  40 ]{.9\columnwidth}{.7\columnwidth}{../Learning/07-09-05_MIPM/figures/mp_movie.mpg}%
  41 \end{frame}%
  42 
  43 \begin{frame}\frametitle{Context: learning to adapt to natural statistics}%
  44 %TODO use notes
  45 %\note Do not talk longer than 2 minutes about this.
  46 \only<1>{%
  47 \begin{columns}%
  48 \begin{column}[c]{.55\textwidth}%
  49 % convert /Users/lup/sci/dyva/lup/Learning/mp_sparsenet/mp_sparsenet/results/20080502T174325/tmp/ssc_0*  ssc_movie.mpg
  50 \includemovie[%
  51 once,text={\includegraphics[width=\linewidth]{fig_map_rand.png}}%controls,../Learning/07-09-05_MIPM/
  52 ]{\textwidth}{\textwidth}{figures/ssc_movie.mpg}%
  53 \end{column}%
  54 \begin{column}{.45\textwidth}%
  55 \end{column}%
  56 \end{columns}%
  57 }%
  58 \only<2>{%
  59 \begin{columns}%
  60 \begin{column}[c]{.55\textwidth}%
  61 	\begin{center}%
  62 		\includegraphics[width=\textwidth]{fig_map_ssc}%
  63 	\end{center}%
  64 \end{column}%
  65 \begin{column}[c]{.45\textwidth}%
  66 	\begin{center}%
  67 		\includegraphics[width=.95\columnwidth]{fig_nonhomeo}%
  68 	\end{center}%
  69 \end{column}%
  70 \end{columns}%
  71 }%
  72 \vspace*{.4cm}%
  73 $\mathcal{C}(\mathbf{s} |\mathbf{x}, \mathbf{A} ) =   \frac{1}{2.\sigma^2}.\|  \mathbf{x} - \sum_j s_j . \mathbf{A}_j \|^2 + \log_2(M) .  \| \mathbf{s} \|_0  $%
  74 \end{frame}
  75 
  76 
  77 %: 2min 
  78 \begin{frame}\frametitle{Context: learning to adapt to natural statistics}%
  79 %\includegraphics<1> [width=1\textwidth]{../Learning/07-09-05_MIPM/figures/laughlin}
  80 \begin{columns}%
  81 \begin{column}{.55\textwidth}%
  82 \begin{center}%
  83 %\includegraphics<2> [width=\textwidth]{../Learning/07-09-05_MIPM/figures/fig_map_perturb_init.png}%
  84 %\includegraphics<3> [width=\textwidth]{../Learning/07-09-05_MIPM/figures/fig_map_perturb_final.png}%
  85 \includegraphics<1> [width=\textwidth]{fig_map_perturb_init.png}%
  86 \includegraphics<2> [width=\textwidth]{fig_map_perturb_final.png}%
  87 \end{center}%
  88 \end{column}
  89 \begin{column}[c]{.45\textwidth}
  90 	%TODO: z should be correlation value
  91 	\includegraphics<1> [width=.95\textwidth]{../Learning/07-09-05_MIPM/figures/fig_perturb_init_P.pdf}%
  92 	\includegraphics<2> [width=.95\textwidth]{../Learning/07-09-05_MIPM/figures/fig_perturb_final_P.pdf}%
  93 \end{column}
  94 \end{columns}
  95 \vspace*{.4cm}%
  96 $\mathcal{C}(\mathbf{s} |\mathbf{x}, \mathbf{A} ) =   \frac{1}{2.\sigma^2}.\|  \mathbf{x} - \sum_j s_j . \mathbf{A}_j \|^2 + \log_2(M) .  \| \mathbf{s} \|_0  $%
  97 \end{frame}
  98 
  99 
 100 %: Following this work, this defined the general thematic for mu research, that is probabilistic representations  
 101 

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  • [get | view] (2014-10-25 13:40:03, 3.1 KB) [[attachment:Annex.tex]]
  • [get | view] (2014-10-25 13:40:03, 3.7 KB) [[attachment:Context.tex]]
  • [get | view] (2014-10-25 13:40:04, 1.4 KB) [[attachment:Makefile]]
  • [get | view] (2014-10-25 13:40:05, 17.3 KB) [[attachment:Motion.tex]]
  • [get | view] (2009-04-14 10:54:25, 35599.0 KB) [[attachment:perrinet09int.pdf]]
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