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-<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Chenran Xu</title><link>https://cr-xu.github.io/</link><atom:link href="https://cr-xu.github.io/index.xml" rel="self" type="application/rss+xml"/><description>Chenran Xu</description><generator>Wowchemy (https://wowchemy.com)</generator><language>en-us</language><lastBuildDate>Thu, 07 Sep 2023 00:00:00 +0000</lastBuildDate><image><url>https://cr-xu.github.io/media/icon_hua7cc9925121b0febe1f9d18384202658_8550_512x512_fill_lanczos_center_3.png</url><title>Chenran Xu</title><link>https://cr-xu.github.io/</link></image><item><title>Bayesian Optimization for SASE Tuning at the European XFEL</title><link>https://cr-xu.github.io/publication/xu-2023-sase/</link><pubDate>Tue, 27 Jun 2023 00:00:00 +0000</pubDate><guid>https://cr-xu.github.io/publication/xu-2023-sase/</guid><description/></item><item><title>Beam trajectory control with lattice-agnostic reinforcement learning</title><link>https://cr-xu.github.io/publication/xu-2023-beam/</link><pubDate>Tue, 27 Jun 2023 00:00:00 +0000</pubDate><guid>https://cr-xu.github.io/publication/xu-2023-beam/</guid><description/></item><item><title>Learning to Do or Learning While Doing: Reinforcement Learning and Bayesian Optimisation for Online Continuous Tuning</title><link>https://cr-xu.github.io/publication/kaiser-2023-learning/</link><pubDate>Tue, 06 Jun 2023 00:00:00 +0000</pubDate><guid>https://cr-xu.github.io/publication/kaiser-2023-learning/</guid><description/></item><item><title>Bayesian optimization of the beam injection process into a storage ring</title><link>https://cr-xu.github.io/publication/xu-2023-bayesian/</link><pubDate>Wed, 01 Mar 2023 00:00:00 +0000</pubDate><guid>https://cr-xu.github.io/publication/xu-2023-bayesian/</guid><description/></item><item><title>Optimization Studies of Simulated THz Radiation at FLUTE</title><link>https://cr-xu.github.io/publication/xu-2022-optimization/</link><pubDate>Fri, 01 Jul 2022 00:00:00 +0000</pubDate><guid>https://cr-xu.github.io/publication/xu-2022-optimization/</guid><description/></item><item><title>Surrogate Modelling of the FLUTE Low-Energy Section</title><link>https://cr-xu.github.io/publication/xu-2022-surrogate/</link><pubDate>Fri, 01 Jul 2022 00:00:00 +0000</pubDate><guid>https://cr-xu.github.io/publication/xu-2022-surrogate/</guid><description/></item><item><title>Transverse and Longitudinal Modulation of Photoinjection Pulses at FLUTE</title><link>https://cr-xu.github.io/publication/nabinger-2022-transverse/</link><pubDate>Fri, 01 Jul 2022 00:00:00 +0000</pubDate><guid>https://cr-xu.github.io/publication/nabinger-2022-transverse/</guid><description/></item><item><title>First Steps Toward an Autonomous Accelerator, a Common Project Between DESY and KIT</title><link>https://cr-xu.github.io/publication/eichler-2021-first/</link><pubDate>Sun, 01 Aug 2021 00:00:00 +0000</pubDate><guid>https://cr-xu.github.io/publication/eichler-2021-first/</guid><description/></item><item><title>Machine Learning Based Spatial Light Modulator Control for the Photoinjector Laser at FLUTE</title><link>https://cr-xu.github.io/publication/xu-2021-machine/</link><pubDate>Sun, 01 Aug 2021 00:00:00 +0000</pubDate><guid>https://cr-xu.github.io/publication/xu-2021-machine/</guid><description/></item><item><title>Example Project</title><link>https://cr-xu.github.io/project/example/</link><pubDate>Wed, 27 Apr 2016 00:00:00 +0000</pubDate><guid>https://cr-xu.github.io/project/example/</guid><description>&lt;p>Lorem ipsum dolor sit amet, consectetur adipiscing elit. Duis posuere tellus ac convallis placerat. Proin tincidunt magna sed ex sollicitudin condimentum. Sed ac faucibus dolor, scelerisque sollicitudin nisi. Cras purus urna, suscipit quis sapien eu, pulvinar tempor diam. Quisque risus orci, mollis id ante sit amet, gravida egestas nisl. Sed ac tempus magna. Proin in dui enim. Donec condimentum, sem id dapibus fringilla, tellus enim condimentum arcu, nec volutpat est felis vel metus. Vestibulum sit amet erat at nulla eleifend gravida.&lt;/p>
+<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Chenran Xu</title><link>https://cr-xu.github.io/</link><atom:link href="https://cr-xu.github.io/index.xml" rel="self" type="application/rss+xml"/><description>Chenran Xu</description><generator>Wowchemy (https://wowchemy.com)</generator><language>en-us</language><lastBuildDate>Thu, 07 Sep 2023 00:00:00 +0000</lastBuildDate><image><url>https://cr-xu.github.io/media/icon_hua7cc9925121b0febe1f9d18384202658_8550_512x512_fill_lanczos_center_3.png</url><title>Chenran Xu</title><link>https://cr-xu.github.io/</link></image><item><title>Tutorials</title><link>https://cr-xu.github.io/tutorials/</link><pubDate>Wed, 21 Feb 2024 00:00:00 +0000</pubDate><guid>https://cr-xu.github.io/tutorials/</guid><description>&lt;p>In recent years, we have given lectures and tutorials on machine topics at various occasions. I have gathered the available ones and provided the link below:&lt;/p>
+&lt;ul>
+&lt;li>&lt;a href="#neural-network-basics">Neural network basics&lt;/a>&lt;/li>
+&lt;li>&lt;a href="#bayesian-optimization">Bayesian optimization&lt;/a>&lt;/li>
+&lt;li>&lt;a href="#reinforcement-learning">Reinforcement Learning&lt;/a>&lt;/li>
+&lt;/ul>
+&lt;h2 id="neural-network-basics">Neural network basics&lt;/h2>
+&lt;ol>
+&lt;li>Tutorial on basic concepts of neural networks using PyTorch, with an example of training a small NN to classify the MNIST dataset. &lt;a href="https://github.com/machine-learning-tutorial/neural-networks" target="_blank" rel="noopener">GitHub Repository&lt;/a>&lt;/li>
+&lt;/ol>
+&lt;h2 id="bayesian-optimization">Bayesian optimization&lt;/h2>
+&lt;ol>
+&lt;li>Tutorial on basic Bayesian optimization techniques with an example for particle accelerator tuning using &lt;code>BoTorch&lt;/code>. &lt;a href="https://github.com/machine-learning-tutorial/bayesian-optimization" target="_blank" rel="noopener">GitHub Repository&lt;/a>&lt;/li>
+&lt;li>The same content was given as a guest lecture in the M.Sc. lecture series &lt;em>Numerical Methods of Accelerator Physics&lt;/em> at TU Darmstadt. &lt;a href="https://github.com/aoeftiger/TUDa-NMAP-14" target="_blank" rel="noopener">2022/23 - Lecture 14&lt;/a> and &lt;a href="https://github.com/aoeftiger/TUDa-NMAP-2023/tree/main/lecture-11" target="_blank" rel="noopener">2023/24 - Lecture 11&lt;/a>&lt;/li>
+&lt;li>Tutorial on basic Bayesian optimization using &lt;code>scikit-learn&lt;/code>, originally given at the 10th MT-ARD-ST3 pre-meeting machine learning workshop &lt;a href="https://indico.desy.de/event/35272/" target="_blank" rel="noopener">(indico link)&lt;/a>. Link to the tutorial &lt;a href="https://github.com/ansantam/2022-MT-ARD-ST3-ML-workshop" target="_blank" rel="noopener">GitHub repository&lt;/a>&lt;/li>
+&lt;/ol>
+&lt;h2 id="reinforcement-learning">Reinforcement Learning&lt;/h2>
+&lt;ol>
+&lt;li>Demonstration of using reinforcement learning to control the linear accelerator ARES, originally given at the RL4AA'23 workshop &lt;a href="https://indico.scc.kit.edu/event/3280/overview" target="_blank" rel="noopener">(indico link)&lt;/a>. Link to the tutorial &lt;a href="https://github.com/RL4AA/RL4AA23" target="_blank" rel="noopener">GitHub repository&lt;/a>&lt;/li>
+&lt;li>Using Meta-RL and GP-MPC to tune the orbit of the AWAKE accelerator, originally given at the RL4AA'24 workshop &lt;a href="https://indico.scc.kit.edu/event/3746/" target="_blank" rel="noopener">(indico link)&lt;/a>. Link to the tutorial &lt;a href="https://github.com/RL4AA/rl4aa24-tutorial" target="_blank" rel="noopener">GitHub repository&lt;/a>&lt;/li>
+&lt;/ol></description></item><item><title>Bayesian Optimization for SASE Tuning at the European XFEL</title><link>https://cr-xu.github.io/publication/xu-2023-sase/</link><pubDate>Tue, 27 Jun 2023 00:00:00 +0000</pubDate><guid>https://cr-xu.github.io/publication/xu-2023-sase/</guid><description/></item><item><title>Beam trajectory control with lattice-agnostic reinforcement learning</title><link>https://cr-xu.github.io/publication/xu-2023-beam/</link><pubDate>Tue, 27 Jun 2023 00:00:00 +0000</pubDate><guid>https://cr-xu.github.io/publication/xu-2023-beam/</guid><description/></item><item><title>Learning to Do or Learning While Doing: Reinforcement Learning and Bayesian Optimisation for Online Continuous Tuning</title><link>https://cr-xu.github.io/publication/kaiser-2023-learning/</link><pubDate>Tue, 06 Jun 2023 00:00:00 +0000</pubDate><guid>https://cr-xu.github.io/publication/kaiser-2023-learning/</guid><description/></item><item><title>Bayesian optimization of the beam injection process into a storage ring</title><link>https://cr-xu.github.io/publication/xu-2023-bayesian/</link><pubDate>Wed, 01 Mar 2023 00:00:00 +0000</pubDate><guid>https://cr-xu.github.io/publication/xu-2023-bayesian/</guid><description/></item><item><title>Optimization Studies of Simulated THz Radiation at FLUTE</title><link>https://cr-xu.github.io/publication/xu-2022-optimization/</link><pubDate>Fri, 01 Jul 2022 00:00:00 +0000</pubDate><guid>https://cr-xu.github.io/publication/xu-2022-optimization/</guid><description/></item><item><title>Surrogate Modelling of the FLUTE Low-Energy Section</title><link>https://cr-xu.github.io/publication/xu-2022-surrogate/</link><pubDate>Fri, 01 Jul 2022 00:00:00 +0000</pubDate><guid>https://cr-xu.github.io/publication/xu-2022-surrogate/</guid><description/></item><item><title>Transverse and Longitudinal Modulation of Photoinjection Pulses at FLUTE</title><link>https://cr-xu.github.io/publication/nabinger-2022-transverse/</link><pubDate>Fri, 01 Jul 2022 00:00:00 +0000</pubDate><guid>https://cr-xu.github.io/publication/nabinger-2022-transverse/</guid><description/></item><item><title>First Steps Toward an Autonomous Accelerator, a Common Project Between DESY and KIT</title><link>https://cr-xu.github.io/publication/eichler-2021-first/</link><pubDate>Sun, 01 Aug 2021 00:00:00 +0000</pubDate><guid>https://cr-xu.github.io/publication/eichler-2021-first/</guid><description/></item><item><title>Machine Learning Based Spatial Light Modulator Control for the Photoinjector Laser at FLUTE</title><link>https://cr-xu.github.io/publication/xu-2021-machine/</link><pubDate>Sun, 01 Aug 2021 00:00:00 +0000</pubDate><guid>https://cr-xu.github.io/publication/xu-2021-machine/</guid><description/></item><item><title>Example Project</title><link>https://cr-xu.github.io/project/example/</link><pubDate>Wed, 27 Apr 2016 00:00:00 +0000</pubDate><guid>https://cr-xu.github.io/project/example/</guid><description>&lt;p>Lorem ipsum dolor sit amet, consectetur adipiscing elit. Duis posuere tellus ac convallis placerat. Proin tincidunt magna sed ex sollicitudin condimentum. Sed ac faucibus dolor, scelerisque sollicitudin nisi. Cras purus urna, suscipit quis sapien eu, pulvinar tempor diam. Quisque risus orci, mollis id ante sit amet, gravida egestas nisl. Sed ac tempus magna. Proin in dui enim. Donec condimentum, sem id dapibus fringilla, tellus enim condimentum arcu, nec volutpat est felis vel metus. Vestibulum sit amet erat at nulla eleifend gravida.&lt;/p>
 &lt;p>Nullam vel molestie justo. Curabitur vitae efficitur leo. In hac habitasse platea dictumst. Sed pulvinar mauris dui, eget varius purus congue ac. Nulla euismod, lorem vel elementum dapibus, nunc justo porta mi, sed tempus est est vel tellus. Nam et enim eleifend, laoreet sem sit amet, elementum sem. Morbi ut leo congue, maximus velit ut, finibus arcu. In et libero cursus, rutrum risus non, molestie leo. Nullam congue quam et volutpat malesuada. Sed risus tortor, pulvinar et dictum nec, sodales non mi. Phasellus lacinia commodo laoreet. Nam mollis, erat in feugiat consectetur, purus eros egestas tellus, in auctor urna odio at nibh. Mauris imperdiet nisi ac magna convallis, at rhoncus ligula cursus.&lt;/p>
 &lt;p>Cras aliquam rhoncus ipsum, in hendrerit nunc mattis vitae. Duis vitae efficitur metus, ac tempus leo. Cras nec fringilla lacus. Quisque sit amet risus at ipsum pharetra commodo. Sed aliquam mauris at consequat eleifend. Praesent porta, augue sed viverra bibendum, neque ante euismod ante, in vehicula justo lorem ac eros. Suspendisse augue libero, venenatis eget tincidunt ut, malesuada at lorem. Donec vitae bibendum arcu. Aenean maximus nulla non pretium iaculis. Quisque imperdiet, nulla in pulvinar aliquet, velit quam ultrices quam, sit amet fringilla leo sem vel nunc. Mauris in lacinia lacus.&lt;/p>
 &lt;p>Suspendisse a tincidunt lacus. Curabitur at urna sagittis, dictum ante sit amet, euismod magna. Sed rutrum massa id tortor commodo, vitae elementum turpis tempus. Lorem ipsum dolor sit amet, consectetur adipiscing elit. Aenean purus turpis, venenatis a ullamcorper nec, tincidunt et massa. Integer posuere quam rutrum arcu vehicula imperdiet. Mauris ullamcorper quam vitae purus congue, quis euismod magna eleifend. Vestibulum semper vel augue eget tincidunt. Fusce eget justo sodales, dapibus odio eu, ultrices lorem. Duis condimentum lorem id eros commodo, in facilisis mauris scelerisque. Morbi sed auctor leo. Nullam volutpat a lacus quis pharetra. Nulla congue rutrum magna a ornare.&lt;/p>

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