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2 changes: 1 addition & 1 deletion 404.html
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<?xml version="1.0" encoding="utf-8"?><feed xmlns="http://www.w3.org/2005/Atom" xml:lang="en"><generator uri="https://jekyllrb.com/" version="4.3.2">Jekyll</generator><link href="epapoutsellis/feed.xml" rel="self" type="application/atom+xml" /><link href="epapoutsellis/" rel="alternate" type="text/html" hreflang="en" /><updated>2023-06-07T09:12:47+00:00</updated><id>epapoutsellis/feed.xml</id><title type="html">blank</title><subtitle>A simple, whitespace theme for academics. Based on [*folio](https://github.com/bogoli/-folio) design.
<?xml version="1.0" encoding="utf-8"?><feed xmlns="http://www.w3.org/2005/Atom" xml:lang="en"><generator uri="https://jekyllrb.com/" version="4.3.2">Jekyll</generator><link href="epapoutsellis/feed.xml" rel="self" type="application/atom+xml" /><link href="epapoutsellis/" rel="alternate" type="text/html" hreflang="en" /><updated>2023-11-19T22:28:55+00:00</updated><id>epapoutsellis/feed.xml</id><title type="html">blank</title><subtitle>A simple, whitespace theme for academics. Based on [*folio](https://github.com/bogoli/-folio) design.
</subtitle><entry><title type="html">CIL on the Cloud</title><link href="epapoutsellis/blog/2023/cil-colab/" rel="alternate" type="text/html" title="CIL on the Cloud" /><published>2023-06-06T15:59:00+00:00</published><updated>2023-06-06T15:59:00+00:00</updated><id>epapoutsellis/blog/2023/cil-colab</id><content type="html" xml:base="epapoutsellis/blog/2023/cil-colab/"><![CDATA[<p>In this blog, we will demonstrate how to use the Core Imaging Library (CIL), an open source software for imaging inverse problems, on cloud platforms like Binder and Google Colab. These platforms offer cloud-based environments with pre-installed packages and resources, making them highly suitable for teaching and training purposes. In addition, if you do not have a GPU or you are a macOS user without GPU or without the right GPU these cloud platforms serve as an excellent alternative. Or maybe you lost connection to your Windows/Linux remote machines and you really want to reconstruct a tomographic dataset.</p>
<h2 id="outline">Outline</h2>
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<th scope="col">Apr, 2023</th>
<th scope="col">Nov, 2023</th>
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<a class="news-title" href="/news/Finden%20Training%20Course/">Finden training course</a>
<strong>Paper:</strong> <a href="https://arxiv.org/abs/2310.01671" rel="external nofollow noopener" target="_blank">A directional regularization method for the limited-angle Helsinki Tomography Challenge using the Core Imaging Library (CIL)</a> was accepted in the <a href="https://www.aimsciences.org/AMMC" rel="external nofollow noopener" target="_blank">Applied Mathematics for Modern Challenges (AMMC)</a>.


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<th scope="col">Apr, 2023</th>
<th scope="col">Nov, 2023</th>
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Invited as a research visitor at the <a href="https://www.newton.ac.uk/event/rntw02/" rel="external nofollow noopener" target="_blank">INI program on Rich and non-linear tomography in medical imaging, materials and non destructive testing</a>, University of Cambridge, March 19 - April 03, 2023.
<strong>Talk:</strong> I gave at talk at the first <a href="https://ccpi.ac.uk/events/first-cil-user-meeting/" rel="external nofollow noopener" target="_blank">CIL User Meeting</a> about “Stochastic Optimisation in CIL”. <a href="/assets/pdf/2023_CIL_User_Meeting_EPapoutsellis_StochasticOpt.pdf">Slides</a>


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<th scope="col">Mar, 2023</th>
<th scope="col">Aug, 2023</th>
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<a class="news-title" href="/news/CIL-Cambridge-Hackathon/">CIL Cambridge Hackathon</a>
<strong>Paper:</strong> <a href="https://arxiv.org/abs/2301.05888" rel="external nofollow noopener" target="_blank">Learning regularization parameter-maps for variational image reconstruction using deep neural networks and algorithm unrolling</a> was accepted in the <a href="https://www.siam.org/publications/journals/siam-journal-on-imaging-sciences-siims" rel="external nofollow noopener" target="_blank">SIAM Journal on Imaging Sciences</a>.


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<th scope="col">Jan, 2023</th>
<th scope="col">Jul, 2023</th>
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<strong>New paper:</strong> <a href="https://arxiv.org/abs/2301.05888" rel="external nofollow noopener" target="_blank">Learning Regularization Parameter-Maps for Variational Image Reconstruction using Deep Neural Networks and Algorithm Unrolling</a>. Amazing collaboration with with Andreas Kofler, Fabian Altekrüger, Fatima Antarou Ba, Christoph Kolbitsch, David Schote, Clemens Sirotenko, Felix Frederik Zimmermann and Kostas Papafitsoros.
Our work on <a href="https://arxiv.org/abs/2304.08350" rel="external nofollow noopener" target="_blank">Unrolled three-operator splitting for parameter-map learning in Low Dose X-ray CT reconstruction</a> was accepted as a Poster presentation at the <a href="https://renaissance.stonybrookmedicine.edu/Fully3D2023" rel="external nofollow noopener" target="_blank">17th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine</a>.


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<th scope="col">Jan, 2023</th>
<th scope="col">Apr, 2023</th>
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<strong>Funding:</strong> Finden was awarded the <a href="https://www.a4i.info/" rel="external nofollow noopener" target="_blank">Analysis for Innovators (A4I) grant</a> in collaboration with the <a href="https://www.npl.co.uk/" rel="external nofollow noopener" target="_blank">National Physical Laboratory</a> for the industrial project <em>Denoising of chemical imaging and tomography data</em>. I will act as a Co-Investigator and work on stochastic and plug and play optimisation.


<a class="news-title" href="/news/Finden%20Training%20Course/">Finden training course</a>
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