.gitignore

@@ -1,315 +0,0 @@
-## Core latex/pdflatex auxiliary files:
-*.aux
-*.lof
-*.log
-*.lot
-*.fls
-*.out
-*.toc
-*.fmt
-*.fot
-*.cb
-*.cb2
-.*.lb
-
-## Intermediate documents:
-*.dvi
-*.xdv
-*-converted-to.*
-# these rules might exclude image files for figures etc.
-# *.ps
-# *.eps
-# *.pdf
-
-## Generated if empty string is given at "Please type another file name for output:"
-.pdf
-
-presentation.pdf
-
-## Bibliography auxiliary files (bibtex/biblatex/biber):
-*.bbl
-*.bbl-SAVE-ERROR
-*.bcf
-*.bcf-SAVE-ERROR
-*.blg
-*-blx.aux
-*-blx.bib
-*.run.xml
-
-## Build tool auxiliary files:
-*.fdb_latexmk
-*.synctex
-*.synctex(busy)
-*.synctex.gz
-*.synctex.gz(busy)
-*.pdfsync
-*.rubbercache
-rubber.cache
-
-## Build tool directories for auxiliary files
-# latexrun
-latex.out/
-
-## Auxiliary and intermediate files from other packages:
-# algorithms
-*.alg
-*.loa
-
-# achemso
-acs-*.bib
-
-# amsthm
-*.thm
-
-# attachfile2
-*.atfi
-
-# beamer
-*.nav
-*.pre
-*.snm
-*.vrb
-
-# changes
-*.soc
-*.loc
-
-# comment
-*.cut
-
-# cprotect
-*.cpt
-
-# elsarticle (documentclass of Elsevier journals)
-*.spl
-
-# endnotes
-*.ent
-
-# fixme
-*.lox
-
-# feynmf/feynmp
-*.mf
-*.mp
-*.t[1-9]
-*.t[1-9][0-9]
-*.tfm
-
-#(r)(e)ledmac/(r)(e)ledpar
-*.end
-*.?end
-*.[1-9]
-*.[1-9][0-9]
-*.[1-9][0-9][0-9]
-*.[1-9]R
-*.[1-9][0-9]R
-*.[1-9][0-9][0-9]R
-*.eledsec[1-9]
-*.eledsec[1-9]R
-*.eledsec[1-9][0-9]
-*.eledsec[1-9][0-9]R
-*.eledsec[1-9][0-9][0-9]
-*.eledsec[1-9][0-9][0-9]R
-
-# glossaries
-*.acn
-*.acr
-*.glg
-*.glo
-*.gls
-*.glsdefs
-*.lzo
-*.lzs
-*.slg
-*.slo
-*.sls
-
-# uncomment this for glossaries-extra (will ignore makeindex's style files!)
-# *.ist
-
-# gnuplot
-*.gnuplot
-*.table
-
-# gnuplottex
-*-gnuplottex-*
-
-# gregoriotex
-*.gaux
-*.glog
-*.gtex
-
-# htlatex
-*.4ct
-*.4tc
-*.idv
-*.lg
-*.trc
-*.xref
-
-# hypdoc
-*.hd
-
-# hyperref
-*.brf
-
-# knitr
-*-concordance.tex
-# TODO Uncomment the next line if you use knitr and want to ignore its generated tikz files
-# *.tikz
-*-tikzDictionary
-
-# listings
-*.lol
-
-# luatexja-ruby
-*.ltjruby
-
-# makeidx
-*.idx
-*.ilg
-*.ind
-
-# minitoc
-*.maf
-*.mlf
-*.mlt
-*.mtc[0-9]*
-*.slf[0-9]*
-*.slt[0-9]*
-*.stc[0-9]*
-
-# minted
-_minted*
-*.data.minted
-*.pyg
-
-# morewrites
-*.mw
-
-# newpax
-*.newpax
-
-# nomencl
-*.nlg
-*.nlo
-*.nls
-
-# pax
-*.pax
-
-# pdfpcnotes
-*.pdfpc
-
-# sagetex
-*.sagetex.sage
-*.sagetex.py
-*.sagetex.scmd
-
-# scrwfile
-*.wrt
-
-# svg
-svg-inkscape/
-
-# sympy
-*.sout
-*.sympy
-sympy-plots-for-*.tex/
-
-# pdfcomment
-*.upa
-*.upb
-
-# pythontex
-*.pytxcode
-pythontex-files-*/
-
-# tcolorbox
-*.listing
-
-# thmtools
-*.loe
-
-# TikZ & PGF
-*.dpth
-*.md5
-*.auxlock
-
-# titletoc
-*.ptc
-
-# todonotes
-*.tdo
-
-# vhistory
-*.hst
-*.ver
-
-# easy-todo
-*.lod
-
-# xcolor
-*.xcp
-
-# xmpincl
-*.xmpi
-
-# xindy
-*.xdy
-
-# xypic precompiled matrices and outlines
-*.xyc
-*.xyd
-
-# endfloat
-*.ttt
-*.fff
-
-# Latexian
-TSWLatexianTemp*
-
-## Editors:
-# WinEdt
-*.bak
-*.sav
-
-# Texpad
-.texpadtmp
-
-# LyX
-*.lyx~
-
-# Kile
-*.backup
-
-# gummi
-.*.swp
-
-# KBibTeX
-*~[0-9]*
-
-# TeXnicCenter
-*.tps
-
-# auto folder when using emacs and auctex
-./auto/*
-*.el
-
-# expex forward references with \gathertags
-*-tags.tex
-
-# standalone packages
-*.sta
-
-# Makeindex log files
-*.lpz
-
-# xwatermark package
-*.xwm
-
-# REVTeX puts footnotes in the bibliography by default, unless the nofootinbib
-# option is specified. Footnotes are the stored in a file with suffix Notes.bib.
-# Uncomment the next line to have this generated file ignored.
-#*Notes.bib

.gitlab-ci.yml

@@ -1,72 +0,0 @@
-variables:
-  # Version de git utilisée
-  GIT_VERSION: v2.30.1
-
-  # Branche cible pour les PDF (modifiable via CI/CD variables)
-  PDF_BRANCH: "pdf"
-
-  FILE_NAMES: presentation
-
-build_tex:
-  stage: build
-  image: danteev/texlive:latest # texlive plus inkscape and others
-  script:
-    - |
-      for FILE_NAME in $FILE_NAMES
-      do
-        echo "Compiling ${FILE_NAME}"
-        pdflatex --shell-escape ${FILE_NAME}.tex
-        if test -f ${FILE_NAME}.bcf; then
-          echo "Found ${FILE_NAME}.bcf, running biber"
-          biber ${FILE_NAME}
-        fi
-        pdflatex --shell-escape ${FILE_NAME}.tex
-      done
-  after_script:
-    - |
-      for FILE_NAME in $FILE_NAMES
-      do
-        echo "============================================"
-        cat ${FILE_NAME}.log
-        echo "============================================"
-      done
-
-  artifacts:
-    paths:
-      - "*.pdf"
-deploy:
-  stage: deploy
-  image:
-    name: alpine/git:${GIT_VERSION}
-    entrypoint: [""]
-
-  before_script:
-    # Clone le repo dans un dossier temporaire
-    - git clone "https://${GITLAB_USERNAME}:${GITLAB_TOKEN}@${CI_SERVER_HOST}/${CI_PROJECT_PATH}.git" "${CI_COMMIT_SHA}"
-
-    # Configure l’identité git
-    - git config --global user.email "${GIT_USER_EMAIL:-$GITLAB_USER_EMAIL}"
-    - git config --global user.name "${GIT_USER_NAME:-$GITLAB_USER_NAME}"
-
-  script:
-    # Déplace les PDFs compilés dans le repo cloné
-    - cd "${CI_COMMIT_SHA}"
-
-    # Crée une branche orpheline (vierge, sans historique ni fichiers)
-    - git checkout --orphan "${PDF_BRANCH}"
-    - git reset --hard
-
-    - mv ../*.pdf ./
-
-    # Ajoute uniquement les PDF
-    - git add -f *.pdf
-
-    # Vérifie s’il y a des changements et push
-    - |
-      CHANGES=$(git status --porcelain | wc -l)
-      if [ "$CHANGES" -gt "0" ]; then
-        git commit -m "${COMMIT_MESSAGE:-Updating PDF files}"
-        git push --force origin "${PDF_BRANCH}" -o ci.skip
-      else
-        echo "No PDF changes to commit"
-      fi

README.md

@@ -1,3 +0,0 @@
-# My presentation for our work on colBiSBM
-
-[The PDF](https://forgemia.inra.fr/louis.lacoste/presentation-colbisbm/-/raw/pdf/presentation.pdf?ref_type=heads)

annexe.tex

@@ -1,203 +0,0 @@
-\section{Clustering}
-
-\begin{frame}{Clustering algorithm}
-    \centering
-    \vspace{0.25\baselineskip}
-    \begin{tikzpicture}[scale=0.85]
-        \input{tikz/clustering.tex}
-    \end{tikzpicture}
-    \[
-        D_{\mathcal{M}}(m,m') = \sum_{q = 1}^{Q_1} \sum_{r = 1}^{Q_2} \max(\widetilde{\pi}_{q}^{m}, \widetilde{\pi}_{q}^{m'}) \left( \widetilde{\alpha}_{qr}^{m} - \widetilde{\alpha}_{qr}^{m'}\right)^{2} \max(\widetilde{\rho}_{r}^{m}, \widetilde{\rho}_{r}^{m'})
-    \]
-\end{frame}
-
-\section{VEM}
-
-\begin{frame}{Developed formula of variational EM}
-    \begin{multline*}
-        \ell (\bm{Y};\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(Y^{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} \eqcolon
-        \mathcal{J}(\tau;\theta),
-    \end{multline*}
-
-    \begin{block}{Variational approximation}
-        $\tau_{iq}^{1,m} = \mathcal{R}^1_{Y^m,\tau}(Z_{iq}^m = 1)$
-        and $\tau_{jr}^{2,m} = \mathcal{R}^2_{Y^m,\tau}(W_{jr}^m = 1)$
-    \end{block}
-\end{frame}
-
-\begin{frame}{\emph{Variational Expectation} Step}
-    \[
-        \widehat{\tau}^{(t+1)} = \arg \max_{\tau}
-        \mathcal{J}(\mathcal{\tau},\bm{\widehat{\theta}}^{(t)})
-        \Leftrightarrow \arg\min_{\tau\in\mathcal{T}} \mathbf{KL}[\mathcal{R}_{\mathbf{Y},\tau}, \mathbb{P}(.|\mathbf{Y})]
-    \]
-
-    \begin{equation*}
-        \begin{cases}
-            \widehat{\tau}_{iq}^{1,m} \propto \widehat{\pi}_{q}^{m(t)} \prod_{j=1}^{n_2^m}\prod_{r\in\mathcal{Q}_2^m} f(Y_{ij}^m;\widehat{\alpha}_{qr}^{(t)})^{\widehat{\tau}_{jr}^{2,m(t+1)}}  & \forall i = 1, \dots , n_1^m, q \in \mathcal{Q}_1^m \\
-            \widehat{\tau}_{jr}^{2,m} \propto \widehat{\rho}_{r}^{m(t)} \prod_{i=1}^{n_1^m}\prod_{q\in\mathcal{Q}_1^m} f(Y_{ij}^m;\widehat{\alpha}_{qr}^{(t)})^{\widehat{\tau}_{iq}^{1,m(t+1)}} & \forall j = 1, \dots , n_2^m, r \in \mathcal{Q}_2^m
-        \end{cases}
-    \end{equation*}
-    \footnotetext[2]{Initialization of $\widehat{\tau}$ with a
-        \emph{spectral clustering} on the networks.}
-\end{frame}
-
-\begin{frame}{\emph{Maximization} Step}
-    \[
-        \widehat{\theta}^{(t+1)} = \arg \max_{\theta} \mathcal{J}(\mathcal{\bm{\widehat{\tau}}}^{(t+1)},\theta)
-    \]
-
-    \begin{block}{Connectivity parameters}
-        \begin{align*}
-            \widehat{\alpha}_{qr} = \frac{\sum_{m=1}^{M} \sum_{i=1}^{n_1^m} \sum_{j=1}^{n_2^m} \tau_{iq}^{1,m} \tau_{jr}^{2,m} \alert<2>{Y_{ij}^m}}{\sum_{m=1}^{M} \sum_{i=1}^{n_1^m} \sum_{j=1}^{n_2^m} \tau_{iq}^{1,m} \tau_{jr}^{2,m}}
-        \end{align*}
-    \end{block}
-    \only<1>{
-        \begin{block}{Proportions for \emph{iid}}
-            \begin{align*}
-                \widehat{\pi}_q = \frac{\sum_{m=1}^{M} \sum_{i=1}^{n_1^m} \tau_{iq}^{1,m}}{\sum_{m=1}^{M} n_1^m} &  &
-                \widehat{\rho}_r = \frac{\sum_{m=1}^{M} \sum_{j=1}^{n_2^m} \tau_{jr}^{2,m}}{\sum_{m=1}^{M} n_2^m}
-            \end{align*}
-        \end{block}
-    }
-    \only<2>{
-        \begin{block}{Proportions for $\pi\rho$}
-            \begin{align*}
-                \widehat{\pi}^{\color{red}m}_q = \frac{\sum_{i=1}^{n_1^m} \tau_{iq}^{1,m}}{n_1^m} &  &
-                \widehat{\rho}^{\color{red}m}_r = \frac{\sum_{j=1}^{n_2^m} \tau_{jr}^{2,m}}{n_2^m}
-            \end{align*}
-        \end{block}
-    }
-
-\end{frame}
-
-\begin{frame}
-    \frametitle{Why does VE minimizes KL ?}
-    \begin{align*}
-        \ell_c(\bY,\bZ,\bW;\theta)                               & = \log \Prob(\bZ, \bW|\bY;\theta) + \ell(\bY;\theta)                                    \\
-        \Leftrightarrow            \ell(\bY;\theta)              & = \ell_c(\bY,\bZ,\bW;\theta) - \log \Prob(\bZ, \bW|\bY;\theta)                          \\
-        \Leftrightarrow            \Esp_{\Ryt}[\ell(\bY;\theta)] & = \Esp_{\Ryt}[\ell_c(\bY,\bZ,\bW;\theta)] - \Esp_{\Ryt}[\log \Prob(\bZ,\bW|\bY;\theta)] \\
-        \Leftrightarrow            \ell(\bY;\theta)              & = \Esp_{\Ryt}[\ell_c(\bY,\bZ,\bW;\theta)] - \Esp_{\Ryt}[\log \Prob(\bZ,\bW|\bY;\theta)] \\
-    \end{align*}
-    \begin{align*}
-        \text{But }\KL{\Ryt}{\log \Prob(\bZ,\bW|\bY;\theta)}                        & = - \Esp_{\Ryt} [\log \frac{\Prob(\bZ,\bW|\bY;\theta)}{\Ryt}] \\
-        = - \Esp_{\Ryt} [\log \Prob(\bZ,\bW|\bY;\theta)] +                          & \underbrace{\Esp_{\Ryt[\log \Ryt]}}_{-\Hshannon(\Ryt)}        \\
-        \Leftrightarrow \KL{\Ryt}{\log \Prob(\bZ,\bW|\bY;\theta)} + \Hshannon(\Ryt) & = - \Esp_{\Ryt} [\log \Prob(\bZ,\bW|\bY;\theta)]
-    \end{align*}
-    Thus $\ell(\bY;\theta) - \KL{\Ryt}{\log \Prob(\bZ,\bW|\bY;\theta)} = \mathcal{J}(\tau;\theta) \qed$
-\end{frame}
-\section{Model selection}
-
-\begin{frame}
-    \frametitle{On the BIC-L}
-    % Raconter l'histoire dans l'ordre suivant :
-    % \begin{itemize}
-    %     \item ICL = Méthode BIC (approx Laplace) sur la log complète, fait apparaître la
-    %           pénalité de complexité et pénalise l'entropie
-    %     \item ICLv = ICL mais avec les paramètres variationnels et l'entropie variationnelle
-    %     \item BIC-L = ICLv mais sans la pénalité sur l'entropie et la rajoutant à la fin
-    % \end{itemize}
-    \begin{align*}
-        % \text{BIC}(\hat{\theta})               & = \log p(\mathbf{Y};\hat{\theta}) - \frac{1}{2} \text{pen}(\dots)                                                                                                                                                                                          \\
-        %                                        & = \Esp_{\mathbf{Z}, \mathbf{W}|\mathbf{Y}} [\underbrace{\log p(\mathbf{Y},\mathbf{Z},\mathbf{W};\hat{\theta})}_{\ell_c(\mathbf{Y},\mathbf{Z},\mathbf{W};\hat{\theta})}] + \mathcal{H}(p(\mathbf{Z},\mathbf{W}|\mathbf{Y})) - \frac{1}{2} \text{pen}(\dots) \\
-        \text{ICL}(\hat{\theta})                                                                                              & = \Esp_{\mathbf{Z}, \mathbf{W}|\mathbf{Y}} [\ell_c(\mathbf{Y},\mathbf{Z},\mathbf{W};\hat{\theta})] - \frac{1}{2} \text{pen}(\dots) \\
-        \Esp_{\mathbf{Z},                       \mathbf{W}|\mathbf{Y}}[\ell_c(\mathbf{Y},\mathbf{Z},\mathbf{W};\hat{\theta})] & =  \log p(\mathbf{Y};\hat{\theta}) - \mathcal{H}(p(\mathbf{Z},\mathbf{W}|\mathbf{Y}))                                              \\
-        \text{And thus,}~\text{ICL}(\hat{\theta})                                                                             & = \log p(\mathbf{Y};\hat{\theta}) - \mathcal{H}(p(\mathbf{Z},\mathbf{W}|\mathbf{Y})) - \frac{1}{2} \text{pen}(\dots)
-    \end{align*}
-    $\mathbf{Z,W|Y}$ intractable, use the \emph{variational approximation} $\mathcal{R}_{\mathbf{Y},\hat{\tau}}$ and don't penalize the entropy we derive the BIC-Like:
-    \[        \text{BIC-L}(\hat{\theta}, \hat{\tau})= \Esp_{\mathcal{R}_{\mathbf{Y}, \hat{\tau}}}[\ell_c(\mathbf{Y},\mathbf{Z},\mathbf{W};\hat{\theta}^{\text{var}})] + \mathcal{H}(\mathcal{R}_{\mathbf{Y}, \hat{\tau}}) - \frac{1}{2} \text{pen}(\dots)
-    \]
-    \cite{biernackiAssessingMixtureModel2000,daudinMixtureModelRandom2008,chabert-liddellLearningCommonStructures2024}
-\end{frame}
-
-\begin{frame}{Practical problems of choosing $Q_1, Q_2$}
-    \begin{alertblock}{Exploration problems}
-        \begin{itemize}
-            \item Sensitivity to initializations. \uncover<2->{$\rightarrow$ \textbf{Spectral
-                          clustering} and \textbf{split \& merge} approach}
-            \item Exploration of a 2D grid is costly. \uncover<3->{$\rightarrow$ \textbf{Greedy
-                          approach} and \textbf{sliding window}}
-        \end{itemize}
-    \end{alertblock}
-\end{frame}
-
-\begin{frame}
-    \frametitle{Choice of $(Q_1,Q_2)$ - Greedy approach}
-    \begin{columns}
-        \begin{column}{0.5\linewidth}
-            \begin{tikzpicture}
-                \input{tikz/greedy-exploration.tex}
-            \end{tikzpicture}
-        \end{column}
-        \begin{column}{0.35\linewidth}
-            \begin{itemize}
-                \item Initial model~: \\ \vspace{0.125\baselineskip}
-                      \begin{tikzpicture}
-                          \draw[fill=gray, draw=gray] circle [radius=0.225cm];
-                      \end{tikzpicture}
-                      \onslide<2->{
-                \item Model after \emph{split}~:
-                      \begin{tikzpicture}
-                          \draw[fill=blueind, draw=blueind] circle [radius=0.225cm];
-                      \end{tikzpicture}
-                \item Model maximizing the criterion~:\\ \vspace{0.125\baselineskip}
-                      \begin{tikzpicture}
-                          \draw[fill=white, draw=green, very thick] circle [radius=0.225cm];
-                      \end{tikzpicture}
-                      }
-                      \onslide<3->{
-                \item Model after \emph{merge}~:
-                      \begin{tikzpicture}
-                          \draw[fill=red, draw=red] circle [radius=0.225cm];
-                      \end{tikzpicture}
-                      }
-            \end{itemize}
-        \end{column}
-    \end{columns}
-\end{frame}
-
-\begin{frame}
-    \frametitle{Choice of $(Q_1,Q_2)$ - Sliding window}
-    \begin{columns}
-        \begin{column}{0.6\textwidth}
-            \begin{figure}
-                \input{tikz/moving-window}
-                \caption{Sliding window}
-            \end{figure}
-        \end{column}
-        \begin{column}{0.4\textwidth}
-            \only<3>{\begin{block}{}
-                    Initialization of the model if necessary
-                \end{block}}
-            \only<9>{\begin{block}{}
-                    Localization of the new mode
-                \end{block}}
-            \only<10>{\begin{block}{}
-                    Move to the new mode then iterate
-                \end{block}}
-        \end{column}
-    \end{columns}
-\end{frame}
-
-\section{Simulations}
-% Ajouter les graphiques de résultats de simulations
-
-\section{Data}
-\begin{frame}
-    \addtocounter{figure}{1}
-    \begin{figure}[ht]
-        \centering
-        \begin{tikzpicture}
-            \tikzset{city/.style={circle, fill=white, draw=red, inner sep=0.65,minimum size=0}}
-            \node (map) at (0,0) {\includegraphics[width=0.35\textwidth]{img/uk-map.png}};
-            \node[city, pin={[pin edge={<-,thick}, pin distance = 25mm]180:Leeds}] (leeds) at (0.2,0.03) {};
-            \node[city, pin={[pin edge={<-,thick}, pin distance = 30mm]0:Edinburgh}] (edinburgh) at (-0.58,1.84) {};
-            \node[city, pin={[pin edge={<-,thick}, pin distance = 20mm]180:Bristol}] (bristol) at (-0.3,-1.82) {};
-            \node[city, pin={[pin edge={<-,thick}, pin distance = 20mm]0:Reading}] (reading) at (0.5,-1.82) {};
-
-        \end{tikzpicture}
-        \caption{Map of the four cities}
-    \end{figure}
-\end{frame}

build-map.R

@@ -1,14 +0,0 @@
-library("leaflet")
-library("mapview")
-library("webshot")
-m <- leaflet() |>
-    addTiles() |>
-    setView(lng = -3.432, lat = 53.1, zoom = 6.4)
-# |>
-# addMarkers(lat = 55.953251, lng = -3.188267, popup = "Edinburgh") |>
-# addMarkers(lat = 51.4545, lng = -2.5879, popup = "Bristol") |>
-# addMarkers(popup = "Leeds", lat = 53.8008, lng = -1.5491) |>
-# addMarkers(popup = "Reading", lat = 51.455, lng = -0.971)
-print(m)
-
-mapshot(m, file = "img/uk-map.png", cliprect = c(20, 365, 395, 600))

dessin-LPM.tex

@@ -1,78 +0,0 @@
-\documentclass[tikz]{standalone}
-\usepackage{tikz}
-\usepackage{xcolor}
-
-\definecolor{lightorange}{HTML}{E69F00}
-\definecolor{darkorange}{HTML}{D55E00}
-\definecolor{lightblue}{HTML}{56B4E9}
-\definecolor{darkblue}{HTML}{0072B2}
-
-
-\usetikzlibrary{trees, positioning, shapes, calc, fit}
-
-\begin{document}
-
-\begin{tikzpicture}[
-        level distance=1.5cm,
-        level 1/.style={sibling distance=4cm},
-        level 2/.style={sibling distance=1.5cm},
-        every node/.style={circle, draw, minimum size=6mm},
-        edge from parent/.style={draw, -latex}
-    ]
-
-    % ======================
-    % ARBRE PHYLOGENETIQUE
-    % ======================
-
-    \node (root) {$i=0$}
-    child {
-            node[fill=lightorange] {$i=1$}
-            child { node[fill=darkorange] {$i=3$} }
-            child { node[fill=darkorange] {$i=4$} }
-            child { node[fill=darkorange] {$i=5$} }
-        }
-    child {
-            node[fill=lightblue] {$i=2$}
-            child { node[fill=darkblue] {$i=6$} }
-            child { node[fill=darkblue] {$i=7$} }
-        };
-
-    % Labels des niveaux
-
-    \node[left=1cm of root-1-1,draw=none] (l2) {$l=2$};
-    \node[above=0.4cm of l2,draw=none] (l1) {$l=1$};
-    \node[above=0.4cm of l1,draw=none] (l0) {$l=0$};
-
-    % ======================
-    % ESPACE LATENT (droite)
-    % ======================
-
-    \begin{scope}[xshift=6cm, yshift=-3.5cm]
-
-        % Axes
-        \draw[->] (-0.5,0) -- (4,0) node[right,draw=none] {};
-        \draw[->] (0,-0.5) -- (0,4) node[above,draw=none] {};
-
-        % Points correspondant aux noeuds
-        \node[inner sep=1.5pt] (g0) at (2,2) {$\gamma_{0,0}$};
-
-        \node[inner sep=1.5pt, left of = g0, fill = lightorange] (g11) {$\gamma_{1,1}$};
-        \node[inner sep=1.5pt, right of = g0, fill = lightblue] (g12) {$\gamma_{1,2}$};
-
-        \node[inner sep=1.5pt, above  = 0.5cm of g11, fill=darkorange]  (g23) {$\gamma_{2,3}$};
-        \node[inner sep=1.5pt, above right = 0.1cm of g23, fill=darkorange]  (g24) {$\gamma_{2,4}$};
-        \node[inner sep=1.5pt, below = 0.5cm of g11, fill=darkorange]  (g25) {$\gamma_{2,5}$};
-
-        \node[inner sep=1.5pt, right = 0.05 cm of g25, fill=darkblue] (g26) {$\gamma_{2,6}$};
-        \node[inner sep=1.5pt, above of = g12, fill=darkblue] (g27) {$\gamma_{2,7}$};
-
-        \path (g0) edge[densely dotted] (g11) edge[densely dotted] (g12);
-        \path (g11) edge[densely dotted] (g23) edge[densely dotted] (g24) edge[densely dotted] (g25);
-        \path (g12) edge[densely dotted] (g27) edge[densely dotted] (g26);
-
-        \node [inner xsep=6pt, inner ysep=3pt, draw = black, fit={(g25) (g26)}, rectangle] {};
-    \end{scope}
-
-\end{tikzpicture}
-
-\end{document}

presentation.tex

@@ -1,150 +0,0 @@
-\documentclass{beamer}
-\usetheme{Boadilla}
-
-% importations
-% \usepackage[french]{babel} % pour dire que le texte est en francais
-\usepackage{csquotes}
-\usepackage[T1]{fontenc} % pour les font postscript
-\usepackage[cyr]{aeguill} % Police vectorielle TrueType, guillemets francais
-\usepackage{epsfig} % pour gérer les images
-\usepackage{amsmath,amsthm, stmaryrd, mathtools} % très bon mode mathématique
-\usepackage{amsfonts,amssymb,bm}% permet la definition des ensembles
-\usepackage{algorithm2e} % pour les algorithmes
-\usepackage{algpseudocode} % pour les algorithmes
-\usepackage{graphicx}
-\usepackage{subcaption}
-\usepackage{float} % pour le placement des figure
-\usepackage{url} % pour une gestion efficace des url
-\usepackage{hyperref}  % pour les hyperliens dans le document
-\usepackage[mode=buildnew]{standalone}
-\usepackage{appendixnumberbeamer} % Cacher la numérotation des slides d'appendices
-\usepackage{beamerappendixnote}
-\usepackage{adjustbox} % To resize tikzpictures
-\usepackage{fontawesome5}
-\usepackage{makecell}
-\usepackage{ccicons}
-
-% Images
-\graphicspath{{./img/}{./figure/}}
-
-% Tikz
-\usepackage{tikz} % For graph plots
-\usepackage[outline]{contour}
-%% Tikz Related
-\usetikzlibrary{calc,shapes,backgrounds,arrows,automata,shadows,positioning}
-\usetikzlibrary{arrows,shapes,positioning,shadows,trees,calc,backgrounds,automata,positioning}
-\usetikzlibrary{decorations.pathreplacing,calligraphy,external,petri, shapes.geometric}
-
-%% Tikz sets
-\tikzset{
-    basic/.style  = {draw, text width=3cm, font=\sffamily, rectangle},
-    root/.style   = {basic, rounded corners=2pt, thin, align=center,
-            fill=green!30},
-    level 2/.style = {basic, rounded corners=6pt, thin,align=center, fill=green!60,
-            text width=8em},
-    level 3/.style = {basic, thin, align=left, fill=pink!60, text width=3.5cm}
-}
-
-% Couleurs
-% pour tickz multilevel
-\usepackage{xcolor}
-\definecolor{aoenglish}{rgb}{0.0, 0.5, 0.0}
-\definecolor{redorg}{RGB}{215, 48, 39}
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-
-%% Couleur Paris-Saclay
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-\definecolor{cyanps}{RGB}{70,195,210}
-\definecolor{vertps}{RGB}{64,183,105}
-%% Biblio
-\usepackage[style=apa, sorting=none, backend=biber]{biblatex}
-\addbibresource{references.bib}
-\AtEveryCite{\color{bluefonceps}}
-\AtEveryBibitem{\clearfield{annotation}} 
-
-\newcommand{\bZ}{\bm{Z}}
-\newcommand{\bY}{\bm{Y}}
-\newcommand{\bW}{\bm{W}}
-\newcommand{\Prob}{\mathbb{P}}
-\newcommand{\Ryt}{\mathcal{R}_{\bY,\tau}}
-\newcommand{\KL}[2]{\mathbf{KL}[#1,#2]}
-\newcommand{\Esp}{\mathbb{E}}
-\newcommand{\Hshannon}{\mathcal{H}}
-
-% Footnote
-\makeatletter
-\newcommand\blfootnote[1]{%
-  \begingroup
-  \renewcommand{\@makefntext}[1]{\noindent\makebox[1.8em][r]#1}
-  \renewcommand\thefootnote{}\footnote{#1}%
-  \addtocounter{footnote}{-1}%
-  \endgroup
-}
-\makeatother
-
-
-% Beamer
-\setbeamertemplate{headline}{%
-    \begin{beamercolorbox}[ht=2.25ex,dp=3.75ex]{section in head/foot}
-        \insertnavigation{\paperwidth}
-    \end{beamercolorbox}%
-}%
-\beamertemplatenavigationsymbolsempty % Pas de bar de navigation
-
-% Beamer settings
-\setbeamertemplate{caption}[numbered]
-\setbeamertemplate{note page}[plain] % Notes
-\setbeamerfont{caption}{size=\scriptsize} % Taille des légendes
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-\setbeamercolor{palette secondary}{bg=blueps, fg=white}
-\setbeamercolor{palette tertiary}{bg=bluefonceps, fg=white}
-\setbeamercolor{structure}{fg=blueps}
-
-
-
-\subtitle{Rochebrune 2026}
-\title[Bipartite networks collection]{Joint estimation of bipartite network collections. Application to plant-pollinator networks.}
-\author[L. Lacoste]{\underline{Louis Lacoste}, Pierre Barbillon and
-Sophie Donnet\newline UMR MIA Paris-Saclay, AgroParisTech, INRAE, Université Paris-Saclay\newline\ccbysa}
-\date{23 mars 2026}
-
-\begin{document}
-
-% titre
-\begin{frame}[noframenumbering,plain]
-    \maketitle
-\end{frame}
-
-\begin{refsection}
-    \include{principal}
-
-    \renewcommand{\pgfuseimage}[1]{\scalebox{.75}{\includegraphics{#1}}}
-    \begin{frame}[noframenumbering,plain,allowframebreaks]
-        \frametitle{References}
-        \printbibliography
-    \end{frame}
-\end{refsection}
-
-\appendix
-
-\begin{refsection}
-    \include{annexe}
-    \renewcommand{\pgfuseimage}[1]{\scalebox{.75}{\includegraphics{#1}}}
-    \section{Appendices references}
-    \begin{frame}[noframenumbering,plain,allowframebreaks]
-        \frametitle{Appendices references}
-        \printbibliography
-    \end{frame}
-\end{refsection}
-
-\end{document}

principal.tex

@@ -1,460 +0,0 @@
-\section{Model Context}
-\label{sec:context-of-the-model}
-\begin{frame}
-    \frametitle{Why \alert<1>{a network?}}
-    \begin{columns}
-        \begin{column}{0.55\textwidth}
-            \begin{columns}
-                \only<1>{
-
-                    \begin{column}{0.5\textwidth}
-
-                        \begin{figure}[ht]
-                            \centering
-                            \begin{tikzpicture}[scale=0.65]
-                                \input{tikz/plantpollinatornetwork.tex}
-                            \end{tikzpicture}
-                            \caption{A toy network}
-                            \label{fig:plants-pollin}
-                        \end{figure}
-                    \end{column}
-                    \begin{column}{0.3\textwidth}
-                        \centering
-                        \begin{align*}
-                            \begin{pmatrix}
-                                1 & 0 & 1 \\
-                                1 & 0 & 0 \\
-                                1 & 0 & 0 \\
-                                1 & 1 & 0
-                            \end{pmatrix}
-                        \end{align*}
-                        \footnotesize
-                        Associated bi-adjacency matrix
-
-                    \end{column}
-                }
-                \only<2>{
-                    \begin{column}{0.5\textwidth}
-                        \begin{figure}[ht]
-                            % \centering
-                            \includegraphics[width=1\textwidth]{tikz/applications/baldock/graph-Baldock2019_Bristol.pdf}
-                            \caption{Plant-pollinator network from
-                                Bristol\newline\cite{baldockSystemsApproachReveals2019}}
-                            \label{fig:bristol-network}
-                        \end{figure}
-                    \end{column}
-                    \begin{column}{0.45\textwidth}
-                        \centering
-                        \begin{figure}
-                            \includegraphics[width=0.7\textwidth]{tikz/applications/baldock/mat-Baldock2019_Bristol.pdf}
-                            \caption{Adjacency matrix of the network}
-                        \end{figure}
-                    \end{column}
-                }
-            \end{columns}
-        \end{column}
-        \begin{column}{0.4\textwidth}
-            \only<1>{
-                \begin{itemize}
-                    \item Bipartite graph $G = (U,V,E)$
-                    \item Encoded in bi-adjacency matrix $Y \in \{0,1\}^{n_1 \times n_2}$
-                \end{itemize}}
-            \only<2>{
-                \begin{itemize}
-                    \item Increasingly available
-                    \item Ecosystems described by their interactions
-                    \item Functional structure for: biodiversity monitoring, robustness, risk of collapse
-                \end{itemize}}
-        \end{column}
-    \end{columns}
-\end{frame}
-
-\begin{frame}{Analysis methods for a network}
-    Several methods~:
-    \begin{itemize}
-        \item Metrics at \begin{itemize}
-                  \item node level: degree, centrality\dots
-                  \item network level: density, nestedness\dots
-              \end{itemize}
-              \cite{kolaczykStatisticalAnalysisNetwork2009}
-        \item \textbf<2>{Node embedding and/or clustering with latent variable models}
-              \\\cite{snijdersEstimationPredictionStochastic1997,hoffLatentSpaceApproaches2002}
-        \item Node or network embedding with Graph Convolutional Networks
-              \\\cite{kipfVariationalGraphAutoEncoders2016a}
-    \end{itemize}
-\end{frame}
-
-\begin{frame}
-    \addtocounter{footnote}{1}
-    \frametitle{Bipartite Stochastic Block Model (BiSBM\footnotemark[\thefootnote])}\framesubtitle{\cite{govaertEMAlgorithmBlock2005}}
-    \begin{columns}
-        \begin{column}{0.40\linewidth}
-            \begin{figure}[H]
-                \center
-                \begin{tikzpicture}[scale=0.35]
-                    \input{tikz/lbm.tex}
-                \end{tikzpicture}
-                \caption{Example of BiSBM}
-                \label{fig:LBMvisu}
-            \end{figure}
-        \end{column}
-        \begin{column}{0.51\linewidth}
-            \begin{block}{Hierarchical model}
-                \vspace{-\baselineskip}
-                \begin{align*}
-                    \forall q\in[\![ 1, Q_1]\!],\mathbb{P}(Z_i = q) = \pi_q   \\
-                    \forall r\in[\![ 1, Q_2]\!],\mathbb{P}(W_j = r) =  \rho_r \\
-                    Y_{ij} | Z_i = q, W_j = r \sim \mathcal{B}ern(\alpha_{q,r})
-                \end{align*}
-                where $|\pi| = Q_1, |\rho| = Q_2, |\alpha| = Q_1 \times Q_2$
-            \end{block}
-            \begin{block}{Concise BiSBM formula}
-                $Y \sim \mathcal{B}ern\text{-BiSBM}_{n_1,n_2}(Q_1, Q_2, \pi, \rho, \alpha)$
-            \end{block}
-        \end{column}
-    \end{columns}
-
-    \footnotetext[\thefootnote]{Commonly Known as \emph{Latent Block Model} (LBM) in the literature.}
-\end{frame}
-
-\begin{frame}
-    \frametitle{How to compare multiple networks?}
-    \begin{figure}[ht]
-        \centering
-        \begin{subfigure}[ht]{0.475\textwidth}
-            \centering
-            \includegraphics[width=0.5\textwidth]{tikz/applications/baldock/mat-Baldock2019_Bristol.pdf}
-            \caption{Bristol}
-        \end{subfigure}
-        \begin{subfigure}[ht]{0.475\textwidth}
-            \centering
-            \includegraphics[width=0.5\textwidth]{tikz/applications/baldock/mat-Baldock2019_Edinburgh.pdf}
-            \caption{Edinburgh}
-        \end{subfigure}
-        \hfill
-        \begin{subfigure}[ht]{0.475\textwidth}
-            \centering
-            \includegraphics[width=0.5\textwidth]{tikz/applications/baldock/mat-Baldock2019_Leeds.pdf}
-            \caption{Leeds}
-        \end{subfigure}
-        \begin{subfigure}[ht]{0.475\textwidth}
-            \centering
-            \includegraphics[width=0.5\textwidth]{tikz/applications/baldock/mat-Baldock2019_Reading.pdf}
-            \caption{Reading}
-        \end{subfigure}
-        \caption{Adjacency matrices,~\cite{baldockSystemsApproachReveals2019}}
-        \label{fig:adj}
-    \end{figure}
-\end{frame}
-
-\section[Bipartite collection models]{Bipartite network collection models}
-\label{sec:extension-of-colsbm-to-bipartite-networks}
-
-\begin{frame}
-    \frametitle{First approach: sep-BiSBM}
-    \only<1-2>{
-        \begin{equation*}
-            \forall m \in \{1\dots M\}, Y^m \overset{ind}{\sim} \mathcal{B}ern\text{-BiSBM}_{n_1^m,n_2^m}(Q_1\alert<2->{^m}, Q_2\alert<2->{^m}, \pi\alert<2->{^m}, \rho\alert<2->{^m}, \alpha\alert<2->{^m})
-        \end{equation*}}
-    \only<3>{
-        \begin{figure}[ht]
-            \centering
-            \begin{subfigure}[ht]{0.42\textwidth}
-                \centering
-                \includegraphics[width=0.5\textwidth]{tikz/applications/baldock/bisbm-mat-Baldock2019_Bristol.pdf}
-                \caption{Bristol, $Q_1 = 3, Q_2 = 3$}
-            \end{subfigure}
-            \begin{subfigure}[ht]{0.42\textwidth}
-                \centering
-                \includegraphics[width=0.5\textwidth]{tikz/applications/baldock/bisbm-mat-Baldock2019_Edinburgh.pdf}
-                \caption{Edinburgh, $Q_1 = 3, Q_2 = 3$}
-            \end{subfigure}
-            \hfill
-            \begin{subfigure}[ht]{0.42\textwidth}
-                \centering
-                \includegraphics[width=0.5\textwidth]{tikz/applications/baldock/bisbm-mat-Baldock2019_Leeds.pdf}
-                \caption{Leeds, $Q_1 = 3, Q_2 = 2$}
-            \end{subfigure}
-            \begin{subfigure}[ht]{0.42\textwidth}
-                \centering
-                \includegraphics[width=0.5\textwidth]{tikz/applications/baldock/bisbm-mat-Baldock2019_Reading.pdf}
-                \caption{Reading, $Q_1 = 3, Q_2 = 3$}
-            \end{subfigure}
-            \caption{Separate BiSBM fit for each network}
-            \label{fig:adj-reord}
-        \end{figure}
-    }
-\end{frame}
-
-\begin{frame}
-    \frametitle{Our contribution: joint models}
-    \onslide<1->{    \begin{block}{\emph{iid}-colBiSBM}
-            \[
-                \forall m \in \{1\dots M\}, Y^m \overset{iid}{\sim}
-                \mathcal{B}ern\text{-BiSBM}_{n_1^m,n_2^m}(Q_1, Q_2, \pi, \rho, \alpha)
-            \]
-
-            with $\theta = (\pi, \rho, \alpha)$.
-        \end{block}}
-    \onslide<2>{    \begin{block}{$\pi\rho$-colBiSBM}
-            \[
-                \forall m \in \{1\dots M\}, Y^m \overset{ind}{\sim}
-                \mathcal{B}ern\text{-BiSBM}_{n_1^m,n_2^m}(Q_1, Q_2, \pi\alert{^m}, \rho\alert{^m}, \alpha)
-            \]
-
-            with $\theta = ((\pi\alert{^m})_{m=1,\dots, M}, (\rho\alert{^m})_{m=1,\dots,
-                        M}, \alpha)$.
-        \end{block}
-    }
-    \begin{itemize}
-        \item No shared nodes across networks
-        \item Agnostic of structure
-    \end{itemize}
-\end{frame}
-% \begin{frame}
-%     \frametitle{Parameter estimation}
-%     % DONE say that tau i q m c' is the probability that Zim = q, approximation of the variational probability. Because we impose independence
-%     % By maximizing a variational lower bound of the
-%     % log-likelihood of the observed data.
-%     Maximizing the log-likelihood?
-%     \begin{block}{log-likelihood and complete log-likelihood}
-%         \[
-%             \ell(\mathbf{Y};\theta) = \sum_{\mathbf{Z,W}\in \mathbf{\mathcal{Z}\times\mathcal{W}}} \ell_c(\mathbf{Y}, \mathbf{Z}, \mathbf{W};\theta)
-%         \]
-
-%         with $\mathbf{\mathcal{Z}} = \{1,\dots,\alert<2>{Q_1}\}^{\alert<2>{n}},
-%             \mathbf{\mathcal{W}} = \{1,\dots,\alert<2>{Q_2}\}^{\alert<2>{n}}$
-%     \end{block}
-%     \uncover<3>{So, classic algorithm $\Rightarrow$
-%         \emph{Expectation-Maximization} (EM).}
-% \end{frame}
-
-% \begin{frame}
-%     \frametitle{By classic EM}
-%     At iteration $(t)$:
-%     \begin{itemize}
-%         \item[$\bullet$]\textbf{E Step}: calculate
-%               $$ \mathcal{Q}(\theta | \theta^{(t-1)}) =   \mathbb E_{\alert<2>{\mathbf Z, \mathbf W | \mathbf Y, \theta^{(t-1)}} } \left[\ell_c(\mathbf Y, \mathbf W, \mathbf Z; \theta)  \right] $$
-%         \item[$\bullet$]\textbf{M Step}:
-%               $$ \theta^{(t)} = \arg \max_{\theta} \mathcal{Q}(\theta | \theta^{(t-1)})$$
-%     \end{itemize}
-%     \uncover<2>{
-%         \begin{alertblock}{Problem for classic EM}
-%             Law of $\mathbf{Z,W|Y},\theta^{(t-1)}$ inaccessible
-%         \end{alertblock}}
-
-% \end{frame}
-\section{Inference and model selection}
-\label{sec:inference-and-model-selection}
-\begin{frame}{Parameter estimation}{How ?}
-    \begin{align*}
-        \ell(\mathbf{Y};\theta) = & \sum_{m=1}^{M} \ell(Y^m;\theta)                                                                                     \\
-        =                         & \sum_{m=1}^{M} \log \sum_{\alert<2->{Z^m \in \mathcal{Z}^m,W^m\in\mathcal{W}^m}} \exp\{\ell_c(Y^m,Z^m,W^m;\theta)\} \\
-        =                         & \sum_{m=1}^{M} \log\sum_{\alert<2->{Z^m \in \mathcal{Z}^m,W^m\in\mathcal{W}^m}}\exp\{\ell(Y^m | Z^m,W^m;\alpha) +   \\
-                                  & \ell(Z^m;\pi) + \ell(W^m;\rho)\}
-        % & = \sum_{m=1}^{M} \sum_{i=1}^{n_1^m} \sum_{q=1}^{Q_1} Z_{iq} \log(\pi_q) + \sum_{j=1}^{n_2^m}\sum_{r=1}^{Q_2} W_{jr} \log(\rho_r) \\
-        % & + \sum_{i,j}\sum_{q,r} Z_{iq}W_{jr} \log \mathcal{B}ern(Y_{ij};\alpha_{qr})
-    \end{align*}
-
-    \onslide<2>{
-        EM impracticable since $\mathbf{Z,W|Y}$ intractable due to
-        conditional dependency.}
-\end{frame}
-\begin{frame}{Parameter estimation}{Solution}
-    \emph{Variational EM}~\cite{daudinMixtureModelRandom2008,chabert-liddellLearningCommonStructures2024}.
-    \begin{block}{Variational approximation of $\mathbf{Z,W|Y}$}
-        $\mathcal{R}_{Y^m,\tau}(Z^m, W^m) =
-            \mathcal{R}^1_{Y^m,\tau}(Z^m)
-            {\color{red}\times}
-            \mathcal{R}^2_{Y^m,\tau}(W^m) \Rightarrow$ independence between rows and columns, mean field approximation.
-    \end{block}
-    \begin{align*}
-        \ell (\mathbf{Y};\theta) \geq \color{red}\sum_{m=1}^{M} \bigg(
-        \color{black} \mathbb{E}_{\mathcal{R}_{Y^m,\tau}(Z^m,W^m)}
-        \left[ \ell_c(Y^m,Z^m,W^m ; \theta) \right] + \\
-        \mathcal{H}(\mathcal{R}_{Y^m,\tau}
-        (Z^m, W^m))
-        \color{red}\bigg) \color{black}
-        \eqcolon \mathcal{J}(\mathcal{R}_{\mathbf{Y},\tau};\theta)
-    \end{align*}
-    where $\theta = (\pi, \rho, \alpha)$ for \emph{iid}-colBiSBM
-\end{frame}
-
-\begin{frame}{Selection criterion for $Q_1, Q_2$}
-    Integrated Classification Likelihood (ICL)~\cite{biernackiAssessingMixtureModel2000}
-    \begin{align*}
-        \text{ICL}(\mathbf{Y}, Q_1, Q_2) & = \mathbb{E}_{\mathbf{Z,W|Y}} [\ell_c(\mathbf{Y,Z,W};\hat{\theta})] -\frac{1}{2}\text{pen}(Q_1, Q_2)                     \\
-                                         & = \ell(\mathbf{Y};\hat{\theta}) - \mathcal{H}(p(\mathbf{Z,W}|\mathbf{Y};\hat{\theta})) - \frac{1}{2}\text{pen}(Q_1, Q_2)
-    \end{align*} For SBM~\cite{daudinMixtureModelRandom2008}.
-    \onslide<2->{
-        \begin{align*}
-            \text{BIC-L}(\mathbf{Y},  Q_1, Q_2) & = \mathbb{E}_{\mathcal{R}_{\mathbf{Y},\hat{\tau}}} [\ell_c(\mathbf{Y,Z,W};\hat{\theta}^{\text{var}})] + \mathcal{H(\mathcal{R}_{\mathbf{Y},\hat{\tau}})} - \frac{1}{2}\text{pen}(Q_1, Q_2) \\
-                                                & = \mathcal{J(\mathcal{R}_{\mathbf{Y},\hat{\tau}}, \hat{\theta}^{\text{var}})} - \frac{1}{2}\text{pen}(Q_1, Q_2)
-        \end{align*}
-    }
-\end{frame}
-
-\section{Application}
-\label{sec:application}
-
-\begin{frame}
-    \frametitle{Results~\cite{baldockSystemsApproachReveals2019}}
-    \only<1>{
-        \begin{figure}[ht]
-            \centering
-            \begin{tikzpicture}[every every node/.style={anchor=south west, inner sep=0pt}, x=1mm, y=1mm]
-                \node (struct) at (0,0) {\includegraphics[width=0.8\textwidth]{tikz/applications/baldock/shared-mixture-iid.pdf}};
-                \node[isosceles triangle,
-                    isosceles triangle apex angle=10,
-                    draw,
-                    rotate=270,
-                    shading = axis,
-                    top color=blue!50,
-                    bottom color=blue!1!white,
-                    anchor=right corner, minimum height=25mm, label={[label distance = 2mm]180:Generalists}, label={[label distance = 2mm]0:Specialists}] (T) at ($(struct.east)+(1.25,8)$) {};
-
-            \end{tikzpicture}
-            \caption{Shared structure ($\alpha$ matrix) and proportions ($\pi$ and $\rho$) of the four networks}
-            \label{fig:shared-mixture}
-        \end{figure}}
-
-    \only<2>{\begin{figure}[ht]
-            \centering
-            \begin{subfigure}[t]{0.5\textwidth}
-                \centering
-                \includegraphics[width=0.45\textwidth]{tikz/applications/baldock/colbisbm-mat-Baldock2019_Bristol.pdf}
-                \caption{Bristol}
-            \end{subfigure}\hfil
-            \begin{subfigure}[t]{0.5\textwidth}
-                \centering
-                \includegraphics[width=0.45\textwidth]{tikz/applications/baldock/colbisbm-mat-Baldock2019_Edinburgh.pdf}
-                \caption{Edinburgh}
-            \end{subfigure}
-            \newline
-            \begin{subfigure}[ht]{0.5\textwidth}
-                \centering
-                \includegraphics[width=0.5\textwidth]{tikz/applications/baldock/colbisbm-mat-Baldock2019_Leeds.pdf}
-                \caption{Leeds}
-            \end{subfigure}\hfil
-            \begin{subfigure}[ht]{0.5\textwidth}
-                \centering
-                \includegraphics[width=0.5\textwidth]{tikz/applications/baldock/colbisbm-mat-Baldock2019_Reading.pdf}
-                \caption{Reading}
-            \end{subfigure}
-            \caption{\emph{iid}-colBiSBM fit, $Q_1 = 3, Q_2 = 5$}
-        \end{figure}}
-\end{frame}
-
-\begin{frame}
-    \frametitle{Focus on Leeds}
-    \captionsetup{font=normalsize}
-    \begin{figure}[ht]
-        \centering
-        \begin{subfigure}[t]{0.5\textwidth}
-            \centering
-            \includegraphics[width=1\textwidth]{tikz/applications/baldock/bisbm-mat-Baldock2019_Leeds.pdf}
-            \caption{sep-BiSBM, $Q_1 = 3, Q_2 = 2$}
-        \end{subfigure}\hfill
-        \begin{subfigure}[t]{0.5\textwidth}
-            \centering
-            \includegraphics[width=1\textwidth]{tikz/applications/baldock/colbisbm-mat-Baldock2019_Leeds.pdf}
-            \caption{\emph{iid}-colBiSBM, $Q_1 = 3, Q_2 = 5$}
-        \end{subfigure}
-    \end{figure}
-\end{frame}
-
-\begin{frame}{\emph{Bombus}}
-    \only<1>{
-        \begin{figure}
-            \captionsetup{font=normalsize}
-            \begin{subfigure}[t]{0.5\textwidth}
-                \centering
-                \includegraphics[width=0.5\textwidth]{img/baldock/bombus-hortorum.jpeg}
-                \caption{\emph{Bombus Hortorum} or garden bumblebee}
-            \end{subfigure}\hfill
-            \begin{subfigure}[t]{0.5\textwidth}
-                \centering
-                \includegraphics[width=0.5\textwidth]{img/baldock/bombus-lapidarius.jpeg}
-                \caption{\emph{Bombus Lapidarius} or red-tailed bumblebee}
-            \end{subfigure}
-        \end{figure}
-    }
-    \only<2->{
-        \begin{columns}
-
-            \begin{column}{0.2\textwidth}
-                \begin{figure}
-                    \onslide<2>{
-                        \begin{subfigure}[t]{0.7\textwidth}
-                            \centering
-                            \includegraphics[width=1\textwidth]{img/baldock/bombus-hortorum.jpeg}
-                            \caption{\emph{Bombus Hortorum} or garden bumblebee}
-                        \end{subfigure}
-                    }
-                    \onslide<3>{
-                        \begin{subfigure}[t]{0.7\textwidth}
-                            \centering
-                            \includegraphics[width=1\textwidth]{img/baldock/bombus-lapidarius.jpeg}
-                            \caption{\emph{Bombus Lapidarius} or red-tailed bumblebee}
-                        \end{subfigure}
-                    }
-                \end{figure}
-            \end{column}
-            \begin{column}{0.7\textwidth}
-                \begin{figure}
-                    \centering
-                    \begin{tikzpicture}[every every node/.style={anchor=south west, inner sep=0pt}, x=1mm, y=1mm]
-                        \node (struct) at (0,0) {\includegraphics[width=0.8\textwidth]{tikz/applications/baldock/shared-iid.pdf}};
-                        \node (gen) at (-29,14.8) {};
-                        \node (interm) at (-29,2.5) {};
-                        \node (spe) at (-29,-9.8) {};
-
-                        \node[left = 3mm of spe] (@aux) {\phantom{B, E, R}};
-
-                        \node[isosceles triangle,
-                            isosceles triangle apex angle=10,
-                            draw,
-                            rotate=270,
-                            shading = axis,
-                            top color=blue!50,
-                            bottom color=blue!1!white,
-                            anchor=right corner, minimum height=42mm, label={[label distance = 2mm]207:Generalists}, label={[label distance = 12mm]357:Specialists}] (T) at ($(struct.north east)+(-1,-2.5)$) {};
-
-                        \only<2>{
-                            \node[left = 3mm of gen] (towns_gen_garden) {B, L};
-                            \node[left = 3mm of spe] (towns_spe_garden) {\phantom{B, }E, R};
-                            \path (towns_gen_garden) edge[->,thick] (gen);
-                            \path (towns_spe_garden) edge[->,thick] (spe);
-                        }
-                        \only<3>{
-                            \node[left = 3mm of interm] (towns_interm_red) {L};
-                            \node[left = 3mm of spe] (towns_spe_red) {B, E, R};
-                            \path (towns_interm_red) edge[->,thick] (interm);
-                            \path (towns_spe_red) edge[->,thick] (spe);
-                        }
-                    \end{tikzpicture}
-                    \caption{Shared structure ($\alpha$ matrix) of the four networks}\label{fig:shared}
-                \end{figure}
-            \end{column}
-        \end{columns}
-    }
-
-\end{frame}
-\section{Conclusion}
-\begin{frame}
-    \frametitle{Conclusion and perspectives}
-    \begin{block}{Summary}
-        \begin{itemize}
-            \item Joint and agnostic structure detection.
-            \item Partitioning algorithm for collections.
-            \item \texttt{R} package \texttt{colSBM} \faGithub~GrossSBM/colSBM.
-            \item An article under review.
-        \end{itemize}
-    \end{block}
-    \begin{block}{Future work: phylogenetic tree and Latent Position Model}
-        \begin{center}
-            \includegraphics[width=0.8\textwidth]{dessin-LPM.pdf}
-        \end{center}
-        \cite{puTreeEnhancedLatentSpace2025,wilmsTreebasedNodeAggregation2022}
-    \end{block}
-\end{frame}