<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Publication | MODE Collaboration</title><link>https://mode-demo.github.io/tags/publication/</link><atom:link href="https://mode-demo.github.io/tags/publication/index.xml" rel="self" type="application/rss+xml"/><description>Publication</description><generator>Hugo Blox Builder (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Mon, 13 May 2024 00:00:00 +0000</lastBuildDate><image><url>https://mode-demo.github.io/media/icon_hu_ebbff252c19052d0.png</url><title>Publication</title><link>https://mode-demo.github.io/tags/publication/</link></image><item><title>Preprint: Optimization Using Pathwise Algorithmic Derivatives</title><link>https://mode-demo.github.io/post/pathwise-derivatives-preprint-2024/</link><pubDate>Mon, 13 May 2024 00:00:00 +0000</pubDate><guid>https://mode-demo.github.io/post/pathwise-derivatives-preprint-2024/</guid><description>&lt;p&gt;The preprint &lt;em&gt;Optimization Using Pathwise Algorithmic Derivatives of Electromagnetic Shower Simulations&lt;/em&gt;, led by several MODE members, is now online.&lt;/p&gt;
&lt;p&gt;&lt;a href="https://arxiv.org/abs/2405.07944" target="_blank" rel="noopener"&gt;Read on arXiv&lt;/a&gt;&lt;/p&gt;</description></item><item><title>TomOpt Paper Accepted by ML: Science and Technology</title><link>https://mode-demo.github.io/post/tomopt-accepted-2024/</link><pubDate>Tue, 07 May 2024 00:00:00 +0000</pubDate><guid>https://mode-demo.github.io/post/tomopt-accepted-2024/</guid><description>&lt;p&gt;The paper &lt;em&gt;TomOpt: Differential optimisation for task- and constraint-aware design of particle detectors in the context of muon tomography&lt;/em&gt; has been accepted for publication by &lt;em&gt;Machine Learning: Science and Technology&lt;/em&gt;.&lt;/p&gt;
&lt;p&gt;&lt;a href="https://arxiv.org/abs/2309.14027" target="_blank" rel="noopener"&gt;Read on arXiv&lt;/a&gt;&lt;/p&gt;</description></item></channel></rss>