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<p class="MsoNormal"><span style="font-size:14.0pt">Welcome to an IDA Machine Learning Seminar on Wednesday, May 17 at 15:15 in Ada Lovelace.</span><o:p></o:p></p>
<p style="margin:0cm;background:white"><b><span style="font-size:16.0pt;color:black"><o:p> </o:p></span></b></p>
<p style="margin:0cm;background:white"><b><span style="font-size:16.0pt;color:black">Scientific Machine Learning - An overview with applications to inverse problems.</span></b><b><span style="font-size:14.0pt;color:black"><br>
</span></b><span class="contentpasted0"><span style="font-size:14.0pt;color:black">Ozan Öktem, The Royal Institute of Technology (KTH), Stockholm </span></span><span class="contentpasted0"><span lang="SV" style="font-size:14.0pt;color:black"><a href="https://www.kth.se/profile/ozan"><span lang="EN-US">https://www.kth.se/profile/ozan</span></a></span></span><span style="font-size:14.0pt;color:black"><o:p></o:p></span></p>
<p class="xxxmsonormal"><b><span style="font-size:8.5pt;font-family:"Verdana",sans-serif;color:black"> </span></b><o:p></o:p></p>
<p style="margin:0cm;background:white"><i><span style="color:black">Abstract:</span></i><span class="MsoHyperlinkFollowed"><span style="font-size:12.0pt;color:black;text-decoration:none">
</span></span><span class="contentpasted0"><span style="font-size:12.0pt;color:black">Scientific Machine Learning is an emerging research area focused on the opportunities and challenges of machine learning in the context of complex applications across science,
engineering, and medicine. Challenges in these fields have attributes that make them very different in nature to computer science applications where data-driven machine learning has found success. The talk will try to provide an overview of Scientific Machine
Learning with emphasis on its recent application to solving large-scale ill-posed inverse problems. <o:p></o:p></span></span></p>
<p style="margin:0cm;background:white"><o:p> </o:p></p>
<p class="xxxmsonormal">Location: <b>Ada Lovelace,</b> <a href="https://www.ida.liu.se/department/location/search.en.shtml?keyword=ada" target="_BLANK">
https://www.ida.liu.se/department/location/search.en.shtml?keyword=ada</a><o:p></o:p></p>
<p class="xxxmsonormal"><span lang="SV">Organizers: Fredrik Lindsten, Sourabh Balgi<o:p></o:p></span></p>
<p class="xxxmsonormal"><span lang="SV"> <o:p></o:p></span></p>
<p class="xxxmsonormal"><span lang="SV">------------------<o:p></o:p></span></p>
<p class="xxxmsonormal"><span lang="SV"> <o:p></o:p></span></p>
<p class="xxxmsonormal">The list of future seminars in the series is available at:
<span lang="SV"><a href="http://www.ida.liu.se/research/machinelearning/seminars/"><span lang="EN-US">http://www.ida.liu.se/research/machinelearning/seminars/</span></a></span><o:p></o:p></p>
<p class="xxxmsonormal">You can subscribe to the seminar series' calendar using this ics link:
<a href="https://outlook.office365.com/owa/calendar/4d811ae47ce446f58d11a7c2f50a7ed8@ad.liu.se/0f5253d7bc7841248c71eb4c28eb2d668927992292494627279/calendar.ics">
https://outlook.office365.com/owa/calendar/4d811ae47ce446f58d11a7c2f50a7ed8@ad.liu.se/0f5253d7bc7841248c71eb4c28eb2d668927992292494627279/calendar.ics</a><o:p></o:p></p>
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