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---
title: Home
description: Braindecode Coding Sprint 2023
image: /images/background.jpg
bottom_image: /images/all-logo.png
map:
latitude: 48.869516
longitude: 2.338116
address: "Université Paris-Saclay, France"
zoom: 13
---
<section class="hero" style="background-image: url({% include relative-src.html src=page.image %})">
<div class="inner-hero text-container">
<div class="hero-text-container">
<center>
<h1 class="editable">Braindecode Code Sprint 2023</h1>
<p class="subtext editable"><b>Starting August 18th, EuroScipy, Basel, Switzerland</b></p>
<p class="subtext editable"><b>Ending September 6th-8th with core meeting 4th-5th, Université Paris-Saclay, France</b></p>
</center>
</div>
</div>
<div class="learn-more">
<a href="#why-what">
<center><p class="subtext editable">Learn more</p>
<img src="https://mne-tools.github.io/sprint2019/images/arrow.gif">
</center></a></div>
</section>
<div class="content" class="container-fluid">
<section class="info" id="why-what">
<div class="container flex">
<div class="text">
<h2 class="editable">Why a code sprint?</h2>
<p class="editable">
Alone you go fast and together we go far!
</p>
<p class="editable">
<a href="https://braindecode.org">Braindecode</a>
is an open-source Python toolbox for decoding raw electrophysiological
brain data with deep learning models. It includes dataset fetchers,
data preprocessing and visualization tools, as well as implementations
of several deep learning architectures and data augmentations for
analysis of EEG, ECoG and MEG.
</p>
<p class="editable">
The primary workhorse of this success has been free open source software (FOSS). With its strong emphasis on API design, the FOSS culture has made it less effortful to plan, develop in teams, re-use, distribute, teach, optimize & scale data analysis efforts. Coding sprints are a way to focus development efforts and share best practices that generalize across a range of application domains.
</p>
<h2 class="editable">What?</h2>
<p class="editable">
The aims of the event are:
<ul>
<li>Restructuring the documentation to make it more accessible for new users.</li>
<li>Re-implement and optimization the DataLoaders.</li>
<li>Re-implement the cropped training.</li>
</ul>
</p>
</div>
</div>
</section>
<section class="pad" id="get-ready">
<div class="container">
<h2 class="editable">Get Ready!</h2>
<p class="editable">
The detailed Pull Requests / Issues tackled during the sprint are described on the <a href="https://github.com/orgs/braindecode/projects/1">Braindecode github project page</a>.
During the sprint, we'll chat on MNE <a href="https://gitter.im/mne-tools/mne-python">discord</a>.
<p class="editable">
</div>
</section>
<section class="pad" id="who">
<div class="container">
<h2 class="editable">Who?</h2>
<ul class="staff">
{% for person in site.staff_members %}
<li>
<div class="square-image" style="background-image: url({% include relative-src.html src=person.image_path %})"></div>
<div class="name"><a target="_blank" href="{{ person.website }}">{{ person.name }}</a></div>
<div class="position">{{ person.blurb }}</div>
</li>
{% endfor %}
</ul>
<!-- <p class="editable">
The current developers focus on <i>neural</i> time series. However, we are particularly interested in productive exchange with other scientific fields that encounter similarly structured signals (finance, musicology, speech processing, climate science, seismology, kinect and radar analyses, etc).
</p>
--> </div>
</section>
<section class="info" id="where-when">
<div class="container">
<div class="text">
<h2 class="editable">Where?</h2>
<p class="editable">EuroScipy, Basel, Switzerland</p>
<p class="editable">Paris-Saclay, France</p>
</div>
</div>
<div class="container">
<div class="text">
<h2 class="editable">When?</h2>
<p class="editable">The sprint will start in August 18th, 2023 and will have an end moment in <September></September> 6-8th with core meeting 4th-5th. You can contribute both virtually and in person.</p>
</div>
</div>
</section>
<section class="contact", id="contact">
<div class="container">
<h2 class="editable">Contact</h2>
<p>b.aristimunha [at] gmail.com</p>
<p>robintibor [at] gmail.com</p>
</div>
</section>
<!-- <section class="achievements", id="achievements">
<div class="container">
<h2 class="editable">Main enhancements</h2>
<p><a href="https://github.com/mne-tools/mne-python/pull/4144">MNE: Add SPoC object to decode continuous targets from oscillatory activity</a></p>
<p><a href="https://github.com/mne-tools/mne-python/pull/3563">MNE: Merge the code of Xdawn and rERP to extract evoked responses from continuous raw signals</a></p>
<p><a href="https://github.com/mne-tools/mne-python/pull/4119">MNE: Use frequency domain for XC/AC optimization in ReceptiveField.</a></p>
<p><a href="https://github.com/mne-tools/mne-python/pull/4139">MNE: Add example of Time-Frequency summary with Global Field Power.</a></p>
<p><a href="https://github.com/mne-tools/mne-python/pull/4115">MNE: Add example of Time-Frequency Decoding based on Common Spatial Pattern.</a></p>
<p><a href="https://github.com/mne-tools/mne-python/pull/4103">MNE: Add scikit-learn compatible SlidingEstimator, GeneralizingEstimator and cross_val_multiscore.</a></p>
<p><a href="https://github.com/mne-tools/mne-python/pull/4110">MNE: Generalize real-time clients and Add LSL real-time client.</a></p>
<p><a href="https://twitter.com/choldgraf/status/848224615960805376">MNE: 3D vizualization in notebook.</a></p>
<p><a href="https://github.com/mne-tools/mne-python/pull/4097">MNE: Improved resolution of favicon ;)</a></p>
<p><a href="https://github.com/glm-tools/pyglmnet/issues/23">pyGLMnet: Add predict_proba method compatible with scikit-learn.</a></p>
<p><a href="https://github.com/glm-tools/pyglmnet/issues/97">pyGLMnet: Add scorers metrics.</a></p>
<p><a href="https://github.com/glm-tools/pyglmnet/issues/158">pyGLMnet: Add GLM and GLMCV estimators.</a></p>
</div>
</section>
-->
<section class="logos", id="logo">
<div class="container">
<div class="text">
<h2 class="editable">Supported by</h2>
</div>
<div class="image">
<img class="editable" src=images/support-logo.png alt="Suported by" />
</div>
<div class="text">
<h2 class="editable">To contribute to</h2>
</div>
<div class="image">
<img class="editable" src=images/contribute-logo.png alt="Suported by" />
</div>
</div>
</section>
</div>