\begin{frame}[noframenumbering] \vfill \centering \begin{beamercolorbox}[sep=8pt,center,shadow=true,rounded=true]{title} \usebeamerfont{title}Annexes\par% \end{beamercolorbox} \vfill \end{frame} \section{Modèles à variables latentes pour collection de réseaux bipartites} \begin{frame} \frametitle{Latent Block Model (LBM)} %DONE remplacer i \in bullet par Zi = \bullet Proposé par~\cite{govaertEMAlgorithmBlock2005}. \begin{columns} \begin{column}{0.40\linewidth} \begin{figure}[H] \center \begin{tikzpicture}[scale=0.35] \input{figures/lbm.tex} \end{tikzpicture} \caption{Exemple de LBM\footnotemark} \label{fig:LBMvisu} \end{figure} \end{column} \begin{column}{0.51\linewidth} Pour \begin{itemize} \item $Q_1 = |\{{\color{blueind}\bullet},{\color{cyanind}\bullet},{\color{electricblue}\bullet}\}|$ blocs fixés en ligne \item $Q_2 = |\{{\color{burntorange}\bullet},{\color{goldenyellow}\bullet},{\color{peach}\bullet}\}|$ blocs fixés en colonne \end{itemize} \begin{block}{Paramètres} \begin{itemize} \item $\pi_{\bullet} = \mathbb{P}(Z_i = \bullet)$ en ligne et $\rho_{\bullet} = \mathbb{P}(W_j = \bullet)$ en colonne \item $\alpha_{{\color{blueind}\bullet}{\color{burntorange}\bullet}} = \mathbb{P}(X_{ij} = 1 | Z_i = {\color{blueind}\bullet}, W_j = {\color{burntorange}\bullet})$ \end{itemize} \end{block} \end{column} \end{columns} \footnotetext{Que j'appellerai par la suite BiSBM} \end{frame} \begin{frame} \frametitle{\emph{colSBM}} Le modèle \emph{colSBM} \parencite{chabert-liddellLearningCommonStructures2023}.\\ % Difficulté estimer les parametres % DONE Modifier les realisations pour variabilite, mettre iid au dessus du sim et inverser modele et realisations \smallskip \definecolor{yellow}{RGB}{255,190,60} \begin{center} \begin{adjustbox}{trim=0 0 0 1cm} \begin{tikzpicture}[scale=.32] \tikzstyle{every edge}=[-,>=stealth',shorten >=1pt,auto,draw,line width=.5pt, bend left] \tikzstyle{every state}=[draw, text=black,scale=0.95, transform shape] \tikzset{edge_proba/.style={draw=white, fill=none, text=black}} \tikzstyle{every node}=[fill=yellow] \node[state, draw=black!50] (A1) at (0,2) {\textbf{A1}}; \node[state, draw=black!50] (A2) at (1.5, 2) {\textbf{A2}}; \node[state, draw=black!50] (A3) at (0.75,3.25) {\textbf{A3}}; \tikzstyle{every node}=[fill=blueind] \node[state, draw=black!50] (B1) at (4.5,3) {\textbf{B1}}; \node[state, draw=black!50] (B2) at (4,4.75) {\textbf{B2}}; \node[state, draw=black!50] (B3) at (5.5,6) {\textbf{B3}}; \node[state, draw=black!50] (B4) at (7,4.75) {\textbf{B4}}; \node[state, draw=black!50] (B5) at (6.5,3) {\textbf{B5}}; \tikzstyle{every node}=[fill=greenind] \node[state, draw=black!50] (C1) at (5,0) {\textbf{C1}}; \node[state, draw=black!50] (C2) at (7,1) {\textbf{C2}}; \path (A1) edge[bend right] (A2); \path (A1) edge node[midway, left, fill=none] {$\alpha_{{\color{yellow}\bullet}{\color{yellow}\bullet}}$} (A3); \path (A3) edge (A2); \path (A3) edge node[midway, above, fill=none] {$\alpha_{{\color{yellow}\bullet}{\color{blueind}\bullet}}$} (B3); \path (B1) edge (B2); \path (B2) edge (B3); \path (B3) edge (B4); \path (B4) edge (B5); \path (B5) edge (B1); \path (B1) edge[bend left=0] (B4); \path (B5) edge[bend left=0] (B2); \path (A2) edge[bend right] node[midway, below, fill=none] {$\alpha_{{\color{yellow}\bullet}{\color{greenind}\bullet}}$} (C1); \path (C1) edge[bend right] node[midway, below, fill=none] {$\alpha_{{\color{greenind}\bullet}{\color{greenind}\bullet}}$} (C2); \path (C2) edge[bend right] node[midway, right, fill=none] {$\alpha_{{\color{greenind}\bullet}{\color{blueind}\bullet}}$} (B4); \node[font=\small, text justified,draw=none, fill=none] at (4.5,-1.5) {SBM}; % Sampled network \begin{scope}[xshift=-16cm,yshift=4cm] \node[font=\small, text justified, fill=none] at (10, -2.5) {$\overset{iid}{\sim}$}; \tikzstyle{every node}=[fill=gray, scale=0.95] \tikzstyle{every edge}=[-,>=stealth',shorten >=1pt,auto,draw,line width=.5pt, bend left] \tikzstyle{every state}=[draw, text=black,scale=0.95, transform shape] \node[state, draw=black!50] (A1) at (0,0) {\textbf{10}}; \node[state, draw=black!50] (A2) at (1, 0) {\textbf{2}}; \node[state, draw=black!50] (A3) at (0.5,1) {\textbf{5}}; \node[state, draw=black!50] (B2) at (2,2.75) {\textbf{9}}; \node[state, draw=black!50] (B3) at (3.5,4) {\textbf{6}}; \node[state, draw=black!50] (B4) at (5,2.75) {\textbf{3}}; \node[state, draw=black!50] (B5) at (4.5,1) {\textbf{7}}; \node[state, draw=black!50] (C1) at (3,-0.5) {\textbf{4}}; \path (A1) edge[bend right] (A2); \path (A1) edge (A3); \path (A3) edge (A2); \path (A3) edge (B3); \path (B2) edge (B3); \path (B3) edge (B4); \path (B4) edge (B5); \path (B5) edge[bend left=0] (B2); \path (A2) edge[bend right] (C1); \node[text width=3cm,font=\small, text justified, rotate=90, fill=none, below = -0.8cm of C1] (dots) {\dots}; \end{scope} \begin{scope}[xshift=-16cm,yshift=-4cm] \tikzstyle{every node}=[fill=gray, scale=0.95] \tikzstyle{every edge}=[-,>=stealth',shorten >=1pt,auto,draw,line width=.5pt, bend left] \tikzstyle{every state}=[draw, text=black,scale=0.95, transform shape] \node[state, draw=black!50] (A2) at (1, 0) {\textbf{2}}; \node[state, draw=black!50] (A3) at (0.5,1) {\textbf{1}}; \node[state, draw=black!50] (B1) at (2.5,1) {\textbf{5}}; \node[state, draw=black!50] (B2) at (2,2.75) {\textbf{10}}; \node[state, draw=black!50] (B4) at (5,2.75) {\textbf{8}}; \node[state, draw=black!50] (B5) at (4.5,1) {\textbf{7}}; \node[state, draw=black!50] (C2) at (5,0) {\textbf{3}}; \path (A3) edge (A2); \path (B1) edge (B2); \path (B4) edge (B5); \path (B5) edge (B1); \path (B1) edge[bend left=0] (B4); \path (B5) edge[bend left=0] (B2); \path (C2) edge[bend right] (B4); \end{scope} \end{tikzpicture} \end{adjustbox} \end{center} Pour $Q = |\{{\color{yellow}\bullet},{\color{blueind}\bullet},{\color{greenind}\bullet}\}|$ blocs fixés : \begin{block}{Paramètres} \begin{itemize} \item $\pi_{\bullet} = \mathbb{P}(Z_i =\bullet)$ \item $\alpha_{{\color{greenind}\bullet}{\color{blueind}\bullet}} = \mathbb{P}(X_{ij} = 1 | Z_i = {\color{greenind}\bullet}, Z_j = {\color{blueind}\bullet})$ \end{itemize} \end{block} \end{frame} \begin{frame} \frametitle{Collections bipartites} \begin{center} \begin{adjustbox}{trim=0 0 1 1.5cm} \begin{tikzpicture}[scale=.33] \begin{scope}[xshift=18cm, yshift=2cm] \input{figures/lbm.tex} \end{scope} \begin{scope}[xshift=3cm, yshift = 1cm] \node[text justified, fill=none] at (10, 3.5) {$\overset{iid}{\sim}$}; \begin{scope}[yshift = 6cm] \tikzstyle{every state}=[draw, text=black,scale=0.75, transform shape] \tikzstyle{every node}=[fill=gray] \node[state, draw=black!50] (R11) at (0,1.25) {\textbf{1}}; \node[state, draw=black!50] (R12) at (1,1.25) {\textbf{2}}; \node[state, draw=black!50] (R13) at (2,1.25) {\textbf{3}}; \node[state, draw=black!50] (R21) at (3,1.25) {\textbf{4}}; \node[state, draw=black!50] (R31) at (5,1.25) {\textbf{6}}; \tikzstyle{every state}=[draw=none,text=black,scale=0.75, transform shape, shape=rectangle] \node[state, draw=black!50] (B1) at (0.5,-1) {\textbf{1}}; \node[state, draw=black!50] (B31) at (2.5,-1) {\textbf{3}}; \node[state, draw=black!50] (B4) at (3.5,-1) {\textbf{4}}; \node[state, draw=black!50] (B5) at (4.5,-1) {\textbf{5}}; \tikzstyle{every edge}=[-,>=stealth',shorten >=1pt,auto,draw,line width=1pt, draw=gray, fill=gray] \path (R11) edge (B1); \path (R11) edge (B31); \path (R11) edge (B4); \path (R12) edge [] (B1); \path (R12) edge (B31); \path (R12) edge (B4); \path (R13) edge [] (B1); \path (R13) edge (B31); \path (R13) edge (B4); \path (R21) edge (B31); \path (R21) edge (B4); \path (R21) edge (B5); \path (R31) edge (B5); \end{scope} \node[text width=3cm,font=\small, text justified, rotate=90, fill=none] (dots) at (2.5, 7.5){\dots}; \begin{scope}[yshift = 0cm] \tikzstyle{every state}=[draw, text=black,scale=0.75, transform shape] \tikzstyle{every node}=[fill=gray] \node[state, draw=black!50] (R11) at (0,2.25) {\textbf{4}}; \node[state, draw=black!50] (R13) at (2,2.25) {\textbf{6}}; \node[state, draw=black!50] (R21) at (3,2.25) {\textbf{3}}; \node[state, draw=black!50] (R22) at (4,2.25) {\textbf{5}}; \node[state, draw=black!50] (R31) at (5,2.25) {\textbf{2}}; \tikzstyle{every state}=[draw=none,text=black,scale=0.75, transform shape, shape=rectangle] \node[state, draw=black!50] (B1) at (0.5,0) {\textbf{5}}; \node[state, draw=black!50] (B2) at (1.5,0) {\textbf{1}}; \node[state, draw=black!50] (B4) at (3.5,0) {\textbf{2}}; \node[state, draw=black!50] (B5) at (4.5,0) {\textbf{4}}; \tikzstyle{every edge}=[-,>=stealth',shorten >=1pt,auto,draw,line width=1pt, draw=gray, fill=gray] \path (R11) edge (B1); \path (R11) edge (B2); \path (R11) edge (B4); \path (R13) edge [] (B1); \path (R13) edge (B2); \path (R13) edge (B4); \path (R21) edge (B4); \path (R21) edge (B5); \path (R22) edge (B4); \path (R22) edge (B5); \path (R31) edge (B5); \end{scope} \end{scope} \end{tikzpicture} \end{adjustbox} \end{center} Pour \begin{itemize} \item $Q_1 = |\{{\color{blueind}\bullet},{\color{cyanind}\bullet},{\color{electricblue}\bullet}\}|$ blocs fixés en ligne \item $Q_2 = |\{{\color{burntorange}\bullet},{\color{goldenyellow}\bullet},{\color{peach}\bullet}\}|$ blocs fixés en colonne \end{itemize} \begin{block}{Paramètres} \begin{itemize} \item $\pi_{\bullet} = \mathbb{P}(Z_i =\bullet)$ en ligne et $\rho_{\bullet} = \mathbb{P}(W_j = \bullet)$ en colonne \item $\alpha_{{\color{blueind}\bullet}{\color{burntorange}\bullet}} = \mathbb{P}(X_{ij} = 1 | Z_i = {\color{blueind}\bullet}, W_j = {\color{burntorange}\bullet})$ \end{itemize} \end{block} \end{frame} \begin{frame} \frametitle{Différents modèles} \begin{block}{\emph{iid-colBiSBM}} $\bm{\pi} = (\pi_1, \dots \pi_{Q_1})$ et $\bm{\rho} = (\rho_1, \dots \rho_{Q_2})$ %{$\forall q \in \llbracket 1, Q_1 - 1\rrbracket, \pi_q > 0$ et $\forall r \in \llbracket 1, Q_2 - 1\rrbracket, \rho_r > 0$} , tous les réseaux partagent les mêmes paramètres\footnotemark \end{block} \begin{block}{\emph{$\pi\rho$-colBiSBM}} $\bm{\pi} = ((\pi_{\color{black}1}^{\color{red}m}, \dots \pi_{\color{black}Q_1}^{\color{red}m}))_{m=1,\dots M}$ et $\bm{\rho} = ((\rho_{\color{black}1}^{\color{red}m}, \dots \rho_{\color{black}Q_2}^{\color{red}m}))_{m=1,\dots M}$ %{$\forall q \in \llbracket 1, Q_1 - 1\rrbracket, \pi_q > 0$ et $\forall r \in \llbracket 1, Q_2 - 1\rrbracket, \rho_r > 0$} \small \\ avec $\forall q,m \in \llbracket 1, Q_1 \rrbracket \times \llbracket 1, M \rrbracket, \pi_q^m \in \left[ 0,1 \right]$ et $\forall r,m \in \llbracket 1, Q_2 \rrbracket \times \llbracket 1, M \rrbracket, \rho_r^m \in \left[ 0,1 \right]$ \end{block} Et également deux autres modèles ($\pi$-colBiSBM et $\rho$-colBiSBM) où seulement une des deux dimensions est libre. \footnotetext{Dans tous les modèles la structure de connectivité est supposée identique au sein de la collection.} \end{frame} \begin{frame} \frametitle{Estimation des paramètres} % DONE dire que tau i q m c' est la proba que Zim = q, approximation de la proba variationnelle. Parce qu on impose lindependance Maximisation d'une borne inférieure de la log-vraisemblance des données observées. \begin{multline*} \ell (\bm{X};\bm{\theta}) \geq \color{red}\sum_{m=1}^{M} \bigg( \color{black} \sum_{i = 1}^{n_1^m}\sum_{j=1}^{n_2^m}\sum_{q \in \mathcal{Q}_{1,m}} \sum_{r \in \mathcal{Q}_{2,m}} \tau^{1,m}_{i,q} \tau^{2,m}_{j,r} \log f(X^{m}_{ij}; \alpha_{qr}) \\ + \sum_{i=1}^{n_1^m} \sum_{q \in \mathcal{Q}_{1,m}} \tau^{1,m}_{i,q} \log \pi_{\color{black}q}^{\color{gray}m} + \sum_{j=1}^{n_2^m} \sum_{r \in \mathcal{Q}_{2,m}} \tau^{2,m}_{j,r} \log \rho_{\color{black}r}^{\color{gray}m} \\ - \sum_{i=1}^{n_1} \tau^{1,m}_{i,q} \log \tau^{1,m}_{i,q} - \sum_{j=1}^{n_2} \tau^{2,m}_{j,r} \log \tau^{2,m}_{j,r} \color{red}\bigg) \color{black} =: J(\bm{\tau};\bm{\theta}) $$ \end{multline*} \begin{block}{Approximation variationnelle} $\tau_{i,q}^{1,m} = P(Z_i = q | X^m_{ij})$ et $\tau_{j,r}^{2,m} = P(W_j = r | X^m_{ij})$ tels que $P(Z_i = q, W_j = r | X^m_{ij}) = \tau_{i,q}^{1,m}\times\tau_{j,r}^{2,m}$ \end{block} \end{frame} \begin{frame} \frametitle{Sélection de modèle : choix de $(Q_1,Q_2)$ - Approche gloutonne} % DONE But maximiser un critere le BICL, deplacer voir St Clair dans la note % VEM a Q1 Q2 fixer % Choix de Q1 Q2 par maximisation du BICL % Itemize dans la box : init, explo voisin, arrets \underline{Le VEM se fait à $Q_1, Q_2$ fixés}, il faut donc déterminer les \enquote*{meilleures} coordonnées. Nous maximisons un BIC-L\footnote{\emph{Bayesian Information Criterion - Like}, en adaptant les formules de~\cite{chabert-liddellLearningCommonStructures2023}}. Détermination d'un premier mode par approche \emph{gloutonne} \smallskip \begin{columns} \begin{column}{0.5\linewidth} \begin{tikzpicture} \draw[step=1cm, help lines] (-2,-2) grid (2,2); \draw[fill=gray, draw=gray] (0,0) circle [radius=0.225cm]; \draw[fill=blueind, draw=blueind] (1,0) circle [radius=0.225cm]; \draw[fill=blueind, draw=blueind] (0,1) circle [radius=0.225cm]; \draw[fill=red, draw=red] (-1,0) circle [radius=0.225cm]; \draw[fill=red, draw=red] (0,-1) circle [radius=0.225cm]; % Légende \node[font=\tiny, text justified,fill=none, rotate=-45] (Splits) at (0.5,0.5){{\color{blueind} Splits}}; \node[font=\tiny, text justified,fill=none, rotate=-45] (Merges) at (-0.5,-0.5){{\color{red} Merges}}; % Splitting \draw[>=stealth,->,thick, draw=blueind] (0.225,0) -- +(0.55,0); \draw[>=stealth,->,thick, draw=blueind] (0,0.225) -- +(0,0.55); % Merging \draw[>=stealth,->,thick, draw=red] (-0.225,0) -- +(-0.55,0); \draw[>=stealth,->,thick, draw=red] (0,-0.225) -- +(0,-0.55); % Axes \draw[>=to,->,thick] (-2,-2) -- +(1,0); \node[font=\small, fill=none] (Q_1) at (-0.75,-2) {$Q_1$}; \draw[>=to,->,thick] (-2,-2) -- +(0,1); \node[font=\small, fill=none] (Q_2) at (-2,-0.75) {$Q_2$}; \end{tikzpicture} \end{column} \begin{column}{0.5\linewidth} \begin{block}{Exploration gloutonne} \begin{itemize} \item Initialisation sur $(1,2)$ et $(2,1)$ \item Exploration des 4 voisins et déplacement sur le meilleur des 4 \item Arrêt après 2 étapes successives sans augmentation du BIC-L \end{itemize} \end{block} \end{column} \end{columns} \end{frame} \begin{frame} \frametitle{Sélection de modèle : choix de $(Q_1,Q_2)$ - Fenêtre glissante} \begin{columns} \begin{column}{0.60\linewidth} \begin{figure} \includegraphics[scale=0.18]{img/moving_window.png} \caption{Exemple de parcours de fenêtre glissante} \end{figure} \end{column} \begin{column}{0.4\linewidth} \definecolor{mypurple}{RGB}{128,0,128} \begin{tikzpicture} \tikzstyle{model}=[circle,draw=none,fill=gray] \tikzstyle{split}=[>=stealth,->,thick, draw=blueind] \tikzstyle{merge}=[>=stealth,->,thick, draw=red] \draw[step=1cm, help lines] (-2,-2) grid (2,2); \node[model] (mode) at (0,0) {{\color{red}X}}; \onslide<2->{ \draw[color=red, line width=1pt] (-1.5,-1.5) rectangle ++(3,3); } \onslide<2-2>{ \node[model] (bottom_left) at (-1,-1) {}; \node[model, opacity=0.6] (row_1) at (0,-1) {}; \node[model, opacity=0.6] (col_1) at (-1,0) {}; \draw[split] (bottom_left) -- (col_1); \draw[split] (-1.75,0) -- (col_1); \draw[split] (bottom_left) -- (row_1); \draw[split] (0,-1.75) -- (row_1); \node[model] (bottom_left) at (-1,-1) {}; \node[model, draw=blue] (row_1) at (0,-1) {}; \node[model, draw=blue] (col_1) at (-1,0) {}; \node[model, opacity=0.6] (row_2) at (1,-1) {}; \node[model, opacity=0.6] (col_2) at (-1,1) {}; \draw[split] (col_1) -- (col_2); \draw[split] (-1.75,1) -- (col_2); \draw[split] (row_1) -- (row_2); \draw[split] (1,-1.75) -- (row_2); \draw[split] (row_1) -- (mode); \draw[split] (col_1) -- (mode); \node[model, draw=blue] (row_2) at (1,-1) {}; \node[model, draw=blue] (col_2) at (-1,1) {}; \node[model, draw=blue] (mode) at (0,0) {{\color{red}X}}; \node[model, opacity=0.6] (row_3) at (1,0) {}; \node[model, opacity=0.6] (col_3) at (0,1) {}; \draw[split] (col_2) -- (col_3); \draw[split] (row_2) -- (row_3); \draw[split] (mode) -- (row_3); \draw[split] (mode) -- (col_3); \node[model, draw=blue] (row_3) at (1,0) {}; \node[model, draw=blue] (col_3) at (0,1) {}; \node[model, opacity=0.6] (top_right) at (1,1) {}; \draw[split] (col_3) -- (top_right); \draw[split] (row_3) -- (top_right); \node[model, draw=blue] (top_right) at (1,1) {}; } \onslide<3->{ \node[model, draw=mypurple] (top_right) at (1,1) {}; \node[model, draw=mypurple] (row_3) at (1,0) {}; \node[model, draw=mypurple] (col_3) at (0,1) {}; \node[model, draw=mypurple] (row_2) at (1,-1) {}; \node[model, draw=mypurple] (col_2) at (-1,1) {}; \node[model, draw=mypurple] (mode) at (0,0) {{\color{red}X}}; \node[model, draw=red] (bottom_left) at (-1,-1) {}; \node[model, draw=mypurple] (row_1) at (0,-1) {}; \node[model, draw=mypurple] (col_1) at (-1,0) {}; \draw[merge] (1,1.75) -- (top_right); \draw[merge] (1.75,1) -- (top_right); \draw[merge] (0,1.75) -- (col_3); \draw[merge] (1.75,0) -- (row_3); \draw[merge] (1.75,-1) -- (row_2); \draw[merge] (-1,1.75) -- (col_2); \draw[merge] (top_right) -- (col_3); \draw[merge] (top_right) -- (row_3); \draw[merge] (col_3) -- (col_2); \draw[merge] (row_3) -- (row_2) ; \draw[merge] (row_3) -- (mode); \draw[merge] (col_3) -- (mode); \draw[merge] (col_2) --(col_1); \draw[merge] (row_2) -- (row_1); \draw[merge] (mode) -- (row_1); \draw[merge] (mode) -- (col_1); \draw[merge] (col_1) -- (bottom_left); \draw[merge] (row_1) -- (bottom_left); } \end{tikzpicture} \end{column} \end{columns} \end{frame} \begin{frame} \frametitle{Clustering de réseaux} \begin{columns} \begin{column}{0.2\linewidth} \begin{block}{Objectif} Déterminer une partition qui maximise la somme du BICL de ses sous-collections. \end{block} \end{column} \begin{column}{0.78\linewidth} \begin{tikzpicture}[scale=0.6, every node/.style={scale=0.75}] \tikzstyle{instruct}=[font=\small, text justified, rectangle,draw,fill=yellow!50] \tikzstyle{first_col}=[rectangle, text justified, draw,fill=gray!50] \tikzstyle{second_col}=[scale=0.55, circle, draw,fill=red!50] \tikzstyle{test}=[font=\small, text justified, diamond, aspect=2.5,thick, draw=blue,fill=yellow!50,text=blue] \tikzstyle{es}=[font=\small, text justified, rectangle,draw,rounded corners=4pt,fill=cyanind!25] \node[es] (liste) at (0,4) {Donner une collection à partitionner}; \node[instruct, text width=5cm, below = 0.45cm of liste] (1-collection) {Ajuster \emph{colBiSBM}}; \node[first_col, right = 0.5cm of 1-collection] (1-col-obj) {}; \node[instruct, text width=5cm, below = 0.45cm of 1-collection] (dissimi) {Calculer une matrice de dissimilarité de la collection}; \node[instruct, text width=5cm, below = 0.45cm of dissimi] (2-sous-collection) {Séparer la \emph{collection en 2 sous-collections} et ajuster les \emph{colBiSBM}}; \node[second_col, right = 0.25cm of 2-sous-collection] (1-sec-col-obj) {1}; \node[second_col, right = 0.25cm of 1-sec-col-obj] (1-sec-col-obj) {2}; \node[test,below = 0.45cm of 2-sous-collection, scale=0.5] (BICL-test) {$\sum_{i=1}^{2} (\text{BIC-L}(\tikz[baseline=-0.25cm]{\node[second_col] {i};} )) > \text{BIC-L}(\tikz[baseline=-0.25cm]{\node[first_col] {};})$?}; \node[es, right = 0.55cm of BICL-test] (sortie) {Renvoyer \tikz{\node[rectangle, draw, fill=gray!50, rounded corners=0pt] {};}}; \node[es, left = 0.45cm of dissimi, text width = 2cm] (recursion) {Recommencer sur \tikz{\node[second_col] {1};} et \tikz{\node[second_col] {2};} }; \tikzstyle{suite}=[->,>=stealth,thick,rounded corners=4pt] \draw[suite] (liste) -- (1-collection); \draw[suite] (1-collection) -- (dissimi); \draw[suite] (dissimi) -- (2-sous-collection); \draw[suite] (2-sous-collection) -- (BICL-test); \draw[suite] (BICL-test) -| node[near start, above, fill=none] {Oui} (recursion); \draw[suite] (recursion.north) |- (1-collection.west); \draw[suite] (BICL-test) -- node[near start, above, fill=none] {Non} (sortie); \end{tikzpicture} \end{column} \end{columns} \blfootnote{Même approche que~\cite{chabert-liddellLearningCommonStructures2023}} \end{frame} \begin{frame} \frametitle{Application, données plantes pollinisateurs} \small Voici des résultats du modèle \emph{iid-colBiSBM} sur des données plantes-pollinisateurs (\cite{doreRelativeEffectsAnthropogenic2021} et~\cite{thebaultDatabasePlantpollinatorNetworks2020}) % DONE Ajouter un tableau avec le nombre de réseaux dans chaque sous-collection \begin{columns} \begin{column}{0.49\linewidth} \includegraphics[scale=0.30]{img/annual_time_span_vs_iid.png} \begin{center} \begin{table} \tiny \begin{tabular}{ |c|c|c|c|c|c| } \hline \thead{N°de \\collection} & 1 & 2 & 3 & 4 & 5 \\ \hline \thead{Nombre de \\réseaux} & 38 & 45 & 1 & 20 & 19 \\ \hline \end{tabular} \end{table} \end{center} \end{column} \begin{column}{0.49\linewidth} \begin{figure}[H] \includegraphics[width=0.45\textwidth]{img/iid-meso-1.png} \includegraphics[width=0.45\textwidth]{img/iid-meso-2.png} \includegraphics[width=0.45\textwidth]{img/iid-meso-3.png} \includegraphics[width=0.45\textwidth]{img/iid-meso-4.png} \includegraphics[width=0.30\textwidth]{img/iid-meso-5.png} \caption{Connectivités de la partition} \end{figure} \end{column} \end{columns} \end{frame} \begin{frame} \frametitle{Perspectives sur \emph{colSBM}} % DONE Ajouter une slide conclusion perspective % Rappeler les modeles avec clustering % Evoquer l'analyse de reseaux corrigés pour l'échantillonnage % Lien vers le package \begin{itemize} \item 4 modèles dont 3 qui ont une flexibilité sur au moins une des dimensions (adaptabilité aux données) \item Partitionner un ensemble de réseaux selon leurs structures \item Comparer les \emph{clusterings} de réseaux obtenus entre données brutes et données corrigées (par exemple par la méthode \emph{CoOPLBM}\footnote{~\cite{anakokDisentanglingStructureEcological2022}}) \end{itemize} \bigskip \centering Le package est disponible sur GitHub : \faGithub \url{https://github.com/Chabert-Liddell/colSBM} \bigskip \end{frame} \section{Autres questions} \begin{frame}{\emph{Message passing} et \emph{Graph Convolutional Network}} TODO Formule Fonction de perte possible \end{frame} \begin{frame}{Distance de Wasserstein} TODO \end{frame}