<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>GCGC website</title><link>https://gcanat.github.io/</link><description>Recent content on GCGC website</description><generator>Hugo</generator><language>en-us</language><copyright>© [Guillaume Canat](https://github.com/gcanat)</copyright><lastBuildDate>Tue, 12 May 2026 00:04:08 +0200</lastBuildDate><atom:link href="https://gcanat.github.io/index.xml" rel="self" type="application/rss+xml"/><item><title>Publications</title><link>https://gcanat.github.io/publications/</link><pubDate>Tue, 12 May 2026 00:04:08 +0200</pubDate><guid>https://gcanat.github.io/publications/</guid><description>&lt;p&gt;&lt;a href="https://doi.org/10.1007/s10815-024-03347-8"&gt;Tackling multinucleation: a call for automated detection in time-lapse embryo monitoring&lt;/a&gt;&lt;/p&gt;
&lt;div class="highlight"&gt;&lt;pre tabindex="0" style="color:#cdd6f4;background-color:#1e1e2e;-moz-tab-size:4;-o-tab-size:4;tab-size:4;-webkit-text-size-adjust:none;"&gt;&lt;code class="language-bib" data-lang="bib"&gt;&lt;span style="display:flex;"&gt;&lt;span&gt;&lt;span style="color:#f9e2af"&gt;@article&lt;/span&gt;{&lt;span style="color:#89dceb"&gt;Nogueira2025&lt;/span&gt;,
&lt;/span&gt;&lt;/span&gt;&lt;span style="display:flex;"&gt;&lt;span&gt;&lt;span style="color:#89b4fa"&gt;author&lt;/span&gt;=&lt;span style="color:#a6e3a1"&gt;{Nogueira, D. and Canat, G. and Gidel-Dissler, N. and Elkhatib, I. and Boussommier, A.}&lt;/span&gt;,
&lt;/span&gt;&lt;/span&gt;&lt;span style="display:flex;"&gt;&lt;span&gt;&lt;span style="color:#89b4fa"&gt;title&lt;/span&gt;=&lt;span style="color:#a6e3a1"&gt;{Tackling multinucleation: a call for automated detection in time-lapse embryo monitoring}&lt;/span&gt;,
&lt;/span&gt;&lt;/span&gt;&lt;span style="display:flex;"&gt;&lt;span&gt;&lt;span style="color:#89b4fa"&gt;journal&lt;/span&gt;=&lt;span style="color:#a6e3a1"&gt;{Journal of Assisted Reproduction and Genetics}&lt;/span&gt;,
&lt;/span&gt;&lt;/span&gt;&lt;span style="display:flex;"&gt;&lt;span&gt;&lt;span style="color:#89b4fa"&gt;year&lt;/span&gt;=&lt;span style="color:#a6e3a1"&gt;{2025}&lt;/span&gt;,
&lt;/span&gt;&lt;/span&gt;&lt;span style="display:flex;"&gt;&lt;span&gt;&lt;span style="color:#89b4fa"&gt;month&lt;/span&gt;=&lt;span style="color:#a6e3a1"&gt;{Jan}&lt;/span&gt;,
&lt;/span&gt;&lt;/span&gt;&lt;span style="display:flex;"&gt;&lt;span&gt;&lt;span style="color:#89b4fa"&gt;day&lt;/span&gt;=&lt;span style="color:#a6e3a1"&gt;{01}&lt;/span&gt;,
&lt;/span&gt;&lt;/span&gt;&lt;span style="display:flex;"&gt;&lt;span&gt;&lt;span style="color:#89b4fa"&gt;volume&lt;/span&gt;=&lt;span style="color:#a6e3a1"&gt;{42}&lt;/span&gt;,
&lt;/span&gt;&lt;/span&gt;&lt;span style="display:flex;"&gt;&lt;span&gt;&lt;span style="color:#89b4fa"&gt;number&lt;/span&gt;=&lt;span style="color:#a6e3a1"&gt;{1}&lt;/span&gt;,
&lt;/span&gt;&lt;/span&gt;&lt;span style="display:flex;"&gt;&lt;span&gt;&lt;span style="color:#89b4fa"&gt;pages&lt;/span&gt;=&lt;span style="color:#a6e3a1"&gt;{345-346}&lt;/span&gt;,
&lt;/span&gt;&lt;/span&gt;&lt;span style="display:flex;"&gt;&lt;span&gt;&lt;span style="color:#89b4fa"&gt;issn&lt;/span&gt;=&lt;span style="color:#a6e3a1"&gt;{1573-7330}&lt;/span&gt;,
&lt;/span&gt;&lt;/span&gt;&lt;span style="display:flex;"&gt;&lt;span&gt;}
&lt;/span&gt;&lt;/span&gt;&lt;/code&gt;&lt;/pre&gt;&lt;/div&gt;&lt;p&gt;&lt;a href="https://www.nature.com/articles/s41598-024-80565-1?utm_source=researchgate.net&amp;amp;utm_medium=article"&gt;A novel deep learning approach to identify embryo morphokinetics in multiple time lapse systems&lt;/a&gt;&lt;/p&gt;
&lt;div class="highlight"&gt;&lt;pre tabindex="0" style="color:#cdd6f4;background-color:#1e1e2e;-moz-tab-size:4;-o-tab-size:4;tab-size:4;-webkit-text-size-adjust:none;"&gt;&lt;code class="language-bib" data-lang="bib"&gt;&lt;span style="display:flex;"&gt;&lt;span&gt;&lt;span style="color:#f9e2af"&gt;@article&lt;/span&gt;{&lt;span style="color:#89dceb"&gt;canat2024novel&lt;/span&gt;,
&lt;/span&gt;&lt;/span&gt;&lt;span style="display:flex;"&gt;&lt;span&gt;&lt;span style="color:#89b4fa"&gt;author&lt;/span&gt;=&lt;span style="color:#a6e3a1"&gt;{Canat, Guillaume and Duval, Antonin and Gidel-Dissler, Nina and Boussommier-Calleja, Alexandra}&lt;/span&gt;,
&lt;/span&gt;&lt;/span&gt;&lt;span style="display:flex;"&gt;&lt;span&gt;&lt;span style="color:#89b4fa"&gt;title&lt;/span&gt;=&lt;span style="color:#a6e3a1"&gt;{A novel deep learning approach to identify embryo morphokinetics in multiple time lapse systems}&lt;/span&gt;,
&lt;/span&gt;&lt;/span&gt;&lt;span style="display:flex;"&gt;&lt;span&gt;&lt;span style="color:#89b4fa"&gt;journal&lt;/span&gt;=&lt;span style="color:#a6e3a1"&gt;{Scientific Reports}&lt;/span&gt;,
&lt;/span&gt;&lt;/span&gt;&lt;span style="display:flex;"&gt;&lt;span&gt;&lt;span style="color:#89b4fa"&gt;year&lt;/span&gt;=&lt;span style="color:#a6e3a1"&gt;{2024}&lt;/span&gt;,
&lt;/span&gt;&lt;/span&gt;&lt;span style="display:flex;"&gt;&lt;span&gt;&lt;span style="color:#89b4fa"&gt;month&lt;/span&gt;=&lt;span style="color:#a6e3a1"&gt;{Nov}&lt;/span&gt;,
&lt;/span&gt;&lt;/span&gt;&lt;span style="display:flex;"&gt;&lt;span&gt;&lt;span style="color:#89b4fa"&gt;day&lt;/span&gt;=&lt;span style="color:#a6e3a1"&gt;{22}&lt;/span&gt;,
&lt;/span&gt;&lt;/span&gt;&lt;span style="display:flex;"&gt;&lt;span&gt;&lt;span style="color:#89b4fa"&gt;volume&lt;/span&gt;=&lt;span style="color:#a6e3a1"&gt;{14}&lt;/span&gt;,
&lt;/span&gt;&lt;/span&gt;&lt;span style="display:flex;"&gt;&lt;span&gt;&lt;span style="color:#89b4fa"&gt;number&lt;/span&gt;=&lt;span style="color:#a6e3a1"&gt;{1}&lt;/span&gt;,
&lt;/span&gt;&lt;/span&gt;&lt;span style="display:flex;"&gt;&lt;span&gt;&lt;span style="color:#89b4fa"&gt;pages&lt;/span&gt;=&lt;span style="color:#a6e3a1"&gt;{29016}&lt;/span&gt;,
&lt;/span&gt;&lt;/span&gt;&lt;span style="display:flex;"&gt;&lt;span&gt;}
&lt;/span&gt;&lt;/span&gt;&lt;/code&gt;&lt;/pre&gt;&lt;/div&gt;&lt;p&gt;&lt;a href="https://www.sciencedirect.com/science/article/pii/S1472648324006825"&gt;Uncovering the association between embryo development and early pregnancy loss using artificial intelligence annotated kinetic events&lt;/a&gt;&lt;/p&gt;</description></item><item><title>About</title><link>https://gcanat.github.io/about/</link><pubDate>Mon, 11 May 2026 23:36:14 +0200</pubDate><guid>https://gcanat.github.io/about/</guid><description>&lt;h2 id="from-finance-to-ml-and-computer-vision"&gt;From finance to ML and Computer Vision&lt;/h2&gt;
&lt;p&gt;Hello, I&amp;rsquo;m Guillaume. I studied mathematics in the early 2000s and worked
in finance for 12+ years. Then I needed a change and decided to go back
to my roots and embrace the inner geek that was always in me :)&lt;/p&gt;
&lt;p&gt;So I went back to school and got an MSc in Machine Learning (Telecom Paris).
This was super fun, I enjoyed so much learning new things in a field that is
both practical and theoretical.&lt;/p&gt;</description></item><item><title>Easy navigation in native Vim</title><link>https://gcanat.github.io/posts/vim-easy-nav/</link><pubDate>Mon, 11 May 2026 23:00:45 +0200</pubDate><guid>https://gcanat.github.io/posts/vim-easy-nav/</guid><description>&lt;h2 id="introduction"&gt;Introduction&lt;/h2&gt;
&lt;p&gt;In the days of fancy plugins super charging vim to make it look like a fully
fledged IDE, I sometimes like to go back to the basics and (re)discover how
vim often already has something builtin to do things, albeit maybe in a
slightly different way.&lt;/p&gt;
&lt;p&gt;Before LSP was a thing, &lt;a href="https://vimhelp.org/tagsrch.txt.html#tags"&gt;tags&lt;/a&gt; were
already there to help us navigate a codebase and we also have the &lt;code&gt;:compiler&lt;/code&gt;
command to run linters and populate the quickfix list with errors.
Before fuzzy finders were all the rage, we already had &lt;code&gt;:edit&lt;/code&gt;, &lt;code&gt;:find&lt;/code&gt; and the
&lt;a href="https://vimhelp.org/editing.txt.html#arglist"&gt;argument list&lt;/a&gt;.&lt;/p&gt;</description></item></channel></rss>