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Update SBI.html and SBIexamples.html
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@kazewong
kazewong committed May 18, 2024
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Expand Up @@ -50,90 +50,7 @@ <h4 class="header">What do we train?</h4>

<section>
<h4 class="header">Normalizing flow</h4>
<div class="row">

</div>
</section>

<!-- Single event inference -->

<section>
<h4 class="header"> Single GW event inference </h4>
<div class="row">
<div class="fragment" style="padding-right: 20px">
<p style="padding:0%; margin:0%;"> Data </p>
<img data-src="../scma8/images/TimeSeries.png" height="360px">
</div>
<div class="fragment" style="padding-right: 20px">
<p style="padding:0%; margin:0%;"> Source properties </p>
<img data-src="../scma8/images/m1m2PE.png" height="360px">
</div>
</div>
</section>

<section>
<h4 class="header ">Neural posterior estimation for gravitational wave</h4>
<div class="row">
<blockquote class="twitter-tweet fragment"><p lang="en" dir="ltr">Can you trust deep learning for scientific inference? And what can you do when results are inaccurate? We address these questions for ML-based inference of complex gravitational wave models and get highly accurate and reliable results. <a href="https://t.co/MLC4HDAv1q">https://t.co/MLC4HDAv1q</a> 1/12 <a href="https://t.co/sK6vJhvWjh">pic.twitter.com/sK6vJhvWjh</a></p>&mdash; Max Dax (@maximilian_dax) <a href="https://twitter.com/maximilian_dax/status/1588177410209742848?ref_src=twsrc%5Etfw">November 3, 2022</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
<div class="column fragment" style="margin-left: 100px;">
<img data-src="https://d3i71xaburhd42.cloudfront.net/284498ac6472eb973ef9bbdd97d2bfb667b7f652/2-Figure1-1.png" width="60%" style="aspect-ratio: auto;">
<img data-src="https://d3i71xaburhd42.cloudfront.net/284498ac6472eb973ef9bbdd97d2bfb667b7f652/14-Figure10-1.png" width="60%" style="aspect-ratio: auto;">

</div>

</div>

</section>

<!-- Unmodelled search-->

<section>
<h4 class="header">Population inference</h4>
<div class="r-stack">
<img class="fragment fade-in-then-out"data-src="https://d3i71xaburhd42.cloudfront.net/1c1ba047fccbeb80fc7c5875a086a3cddc98dab4/4-Figure2-1.png" width="70%">
<div class="row">
<div class="column fragment">
<img data-src="https://d3i71xaburhd42.cloudfront.net/85920220d916aa96e5ef7f4f8eeca6152499a235/3-Figure1-1.png" width="100%">
</div>
<div class="column fragment">
<img data-src="https://d3i71xaburhd42.cloudfront.net/85920220d916aa96e5ef7f4f8eeca6152499a235/4-Figure3-1.png" width="100%">
</div>
<div class="fragment">
<iframe width="720" height="500" src="https://www.youtube.com/embed/s27I7b3-FMY?start=30" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe>
</div>

</div>
<p style="color: white;" class="fragment">If you believe us, then most of the bbhs are from cluster!<span class="fragment" style="font-size: medium; color: tomato; text-align: center; ">(I don't)</span></p>
</section>

<section>
<h3>Let's take a moment and think</h3>
<h4 class="fragment"> why the first example is more believable?</h4>
</section>

<section>
<h3 class="header">Lesson from two SBI scenarios</h4>
<div class="column">
<div class="row" style="justify-content: space-between;">
<div class="column" style="color: skyblue;">
<h4 class="fragment" style="color: skyblue;">Perks of SBI</h4>
<ol>
<li class="fragment">Fast inference</li>
<li class="fragment">Low retuning human effort</li>
<li class="fragment">Flexible assumptions</li>
</ol>
</div>
<div class="column" style="color: tomato;">
<h4 class="fragment" style="color: tomato;">Dangers of SBI</h4>
<ol>
<li class="fragment">"Why is my mass negative"</li>
<li class="fragment">Are we really winning?</li>
<li class="fragment">Retraining cost</li>
</ol>
</div>
</div>
<div class="column" style="margin-top: 30px;">
<p class="fragment" style="margin: 3px; color: skyblue;">Fixed model, changing data -> Good </p>
<p class="fragment" style="margin: 3px; color: tomato;">Fixed data, change model -> Bad </p>
</div>
</div>

</section>

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