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---
layout: single
author_profile: false
---
Welcome to the webpage of the Approximate Bayesian Inference Team @ <a href="https://www.riken.jp/en/research/labs/aip/">RIKEN AIP</a>.
<br>
<br>
<div class="highlights">
<div class="slick-slide">
<iframe width="560" height="315" src="https://www.youtube.com/embed/_49ydwCrhVk?si=6E6O4kPijCMW-FyY" frameborder="0" allow="accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture"
allowfullscreen></iframe>
Keynote at the <a href="https://lifelong-ml.cc/" target="_blank">3rd Conference on Lifelong Learning Agents (CoLLAs) 2024</a> [ <a href="https://emtiyaz.github.io/papers/July30_2024_CoLLAs.pdf" target="_blank">Slides</a> ]
</div>
<div class="slick-slide">
<iframe width="560" height="315" src="https://www.youtube.com/embed/SynayJaFIrI?start=3426" frameborder="0" allow="accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture"
allowfullscreen></iframe>
<a
href="https://arxiv.org/abs/2402.17641">ICML 2024: Variational Learning is Effective for Large Deep Networks</a>
</div>
<div class="slick-slide">
<iframe width="560" height="315" src="https://www.youtube.com/embed/4T_E5IO3aBI?rel=0" frameborder="0" allow="accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture"
allowfullscreen></iframe>
<a
href="https://arxiv.org/abs/2210.01620">ICLR 2023: SAM as an Optimal Relaxation of Bayes</a>
</div>
<div class="slick-slide">
<video controls style="width: 100%; height: 100%;">
<source src="https://download.dsf.tuhh.de/ig4ds22/videos/IG4DS-GeoffreyWolfer_Information_Geometry.mp4" type="video/mp4">
Your browser does not support the video tag.
</video>
Talk at <a href="https://www.dsf.tuhh.de/index.php/ig4ds/" target="_blank">IG4DS</a> -
"Information Geometry of Reversible Markov Chains" [ <a href="https://download.dsf.tuhh.de/ig4ds22/slides/IG4DS-GeoffreyWolfer-Information.pdf" target="_blank">Slides</a> ]
</div>
<div class="slick-slide">
<img src="assets/images/kpriors.png">
<a href="https://slideslive.com/38959794/kpriors-a-general-principle-of-adaptation?ref=speaker-17205-latest">
K-priors: A General Principle of Adaptation</a>
</div>
<div class="slick-slide">
<iframe width="560" height="315" src="https://www.youtube.com/embed/XvTFW0MqtZE" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture"
allowfullscreen></iframe>
<a href="https://aip.riken.jp/video/aip-open-seminar-16/">RIKEN AIP Open Seminar 2021</a>
</div>
<div class="slick-slide">
<img src="assets/images/bayesian.png">
<a
href="https://arxiv.org/abs/2107.04562">The
Bayesian Learning Rule</a>
</div>
<div class="slick-slide">
<iframe width="560" height="315" src="https://www.youtube.com/embed/2DqFApSP2xQ?rel=0" frameborder=0" allow="accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture"
allowfullscreen></iframe>
Tutorial at SMILES 2020: <a href="https://emtiyaz.github.io/papers/learning_from_bayes.pdf">Learning with Bayesian Principles.</a>
</div>
<div class="slick-slide">
<iframe width="560" height="315" src="https://www.youtube.com/embed/xp_UCGVMPIM?rel=0" frameborder=0" allow="accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture"
allowfullscreen></iframe>
Tutorial at SMILES 2020: Sequential Prediction Problems.
</div>
<div class="slick-slide">
<img src="assets/images/research2019.png">
<a href="https://emtiyaz.github.io/papers/symposium_2019.pdf"> Summary of our research work for the year 2019. </a>
</div>
<div class="slick-slide">
<iframe width="560" height="315" src="https://www.youtube.com/embed/2wFb46Q8kmA" frameborder="0" allow="accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture"
allowfullscreen></iframe>
<a href="https://nips.cc/Conferences/2019/Schedule?showEvent=13205" target="_blank">NeurIPS 2019 Tutorial</a>. See <a href="papers/neurips_tutorial.pdf" target="_blank">Slides</a>, <a href="https://slideslive.com/38921489/deep-learning-with-bayesian-principles" target="_blank">on SlidesLive</a> or <a href="https://www.youtube.com/watch?v=2wFb46Q8kmA"
target="_blank">YouTube</a>.
</div>
</div>
<div>
<script type="text/javascript" src="//code.jquery.com/jquery-1.11.0.min.js"></script>
<script type="text/javascript" src="//code.jquery.com/jquery-migrate-1.2.1.min.js"></script>
<script type="text/javascript" src="slick/slick.min.js"></script>
<script type="text/javascript">
$('.highlights').slick({
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slidesToShow: 3,
slidesToScroll: 1,
accessibility: true,
mobileFirst: true,
arrows: true,
});
</script>
</div>
<br>
Humans, animals, and other living beings have a natural ability to autonomously learn throughout their lives and quickly adapt to their surroundings, but computers lack such abilities.
Our goal is to bridge such gaps between the learning of living-beings and computers.
We are machine learning researchers with an expertise in areas such as approximate inference, Bayesian statistics, continuous optimization, information geometry, etc.
We work on a variety of learning problems, especially those involving supervised, continual, active, federated, online, and reinforcement learning. Please check out
<a href="../research/">research</a> and <a href="../publications">publications</a> pages for a more exhaustive overview.
<br><br>
If you are interested in joining us, see the <a href="../people">people</a> page and the news below for current opportunities.
<br><br>
<div>
<h1>News</h1>
{% for post in site.posts %}
{% if post.categories contains 'pinned-news' %}
<div class="news">
<b class="news-title"> <i class="fa fa-thumbtack"></i> <b> {{ post.title }} </b> </b> <br>
{{ post.content }}
<hr>
</div>
{% endif %}
{% endfor %}
{% assign i = 0 %}
{% for post in site.posts %}
{% if post.categories contains 'news' and i < 5 %}
<div class="news">
<b class="news-title"> <i class="fa {{post.logo}}"></i> <b> {{ post.date | date: '%B %d, %Y' }} </b> </b> <br>
{{ post.content }}
<hr>
</div>
{% assign i = i | plus:1 %}
{% endif %}
{% endfor %}
<a href="news" class="news"> Show older news... </a>
</div>