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<div>---------- Forwarded message ---------<br>
De: <span class="gmail_sendername">FRIB User Contact</span> <span dir="ltr"><<a href="mailto:fribusercontact@fribusers.org" target="_blank" id="LPlnk280271" class="OWAAutoLink" previewremoved="true">fribusercontact@fribusers.org</a><wbr>></span><br>
Date: dv., 12 d’abr. 2019 a les 7:53<br>
Subject: Summer School Announcement: Machine Learning Applied to Nuclear Physics<br>
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<p class="MsoNormal"><b><span style="font-size:11.0pt;font-family:"Calibri",sans-serif">Announcing a FRIB-Theory Alliance Summer School: “</span></b><span style="font-size:11.0pt;font-family:"Calibri",sans-serif">Machine Learning Applied to Nuclear Physics”</span></p>
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<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri",sans-serif">Machine Learning is one of the most exciting and dynamic areas of modern research and application. The purpose of this summer school is to provide an introduction to the core
concepts and tools of machine learning in a manner easily understood and intuitive to physicists and nuclear physicists in particular. We will start with some of the basic methods from supervised learning, such as various regression methods before we move
into deep learning methods for both supervised and unsupervised learning, with an emphasis on the analysis of nuclear physics experiments and theoretical nuclear physics. </span></p>
<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri",sans-serif">Hands-on examples will be provided and the aim is to give the participants an overview on how machine learning can be used to analyze and study nuclear physics problems. </span></p>
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<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri",sans-serif">Lecturers:</span></p>
<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri",sans-serif">Morten Hjorth-Jensen (FRIB/NSCL and Physics & Astronomy MSU) - Linear and logistic regression, decision trees and random forests, neural networks and Boltzmann machines</span></p>
<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri",sans-serif">Matthew Hirn (CSME and Math MSU) - Unsupervised learning and quantum mechanical problems</span></p>
<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri",sans-serif">Michelle Kuchera (Davidson College) -<span class="m_-3791757179141911365m_1101704141267793329gmail-m-1015916662098528186apple-converted-space"> </span>Convolutional Neural
Networks, Recurrent Neural Networks and analysis of nuclear physics experiments</span></p>
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<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri",sans-serif">Date and location:</span></p>
<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri",sans-serif">May 20-23, 2019 at the FRIB, East Lansing, MI</span></p>
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<span style="font-size:11.0pt;font-family:"Calibri",sans-serif">For more information and to apply for the summer school visit the<span class="m_-3791757179141911365m_1101704141267793329gmail-m-1015916662098528186apple-converted-space"> </span></span><span class="m_-3791757179141911365m_1101704141267793329gmail-m-1015916662098528186msohyperlink"><span style="font-family:"Calibri",sans-serif;color:#0563c1"><a href="https://indico.frib.msu.edu/event/16/" target="_blank" data-saferedirecturl="https://www.google.com/url?q=https://indico.frib.msu.edu/event/16/&source=gmail&ust=1555173989366000&usg=AFQjCNEXzrH30ijlkZnmjpXHBCAB2sDeTw" id="LPlnk148359" class="OWAAutoLink" previewremoved="true"><span style="font-size:11.0pt;color:#954f72">website</span></a>.</span></span><br>
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