BEGIN:VCALENDAR
PRODID:KIT-Zentrum MathSEE
VERSION:2.0
X-WR-CALNAME:KIT-Zentrum MathSEE
NAME:KIT-Zentrum MathSEE
REFRESH-INTERVAL;VALUE=DURATION:PT12H
X-PUBLISHED-TTL:PT12H
BEGIN:VTIMEZONE
TZID:Europe/Berlin
TZURL:http://tzurl.org/zoneinfo-outlook/Europe/Berlin
X-LIC-LOCATION:Europe/Berlin
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:19700329T020000
RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=-1SU
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TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:19701025T030000
RRULE:FREQ=YEARLY;BYMONTH=10;BYDAY=-1SU
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BEGIN:VEVENT
UID: 63101
DTSTAMP:20261030T195923Z
SUMMARY:MathSEE Members Assembly
X-ALT-DESC;FMTTYPE=text/html:<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 
 3.2//EN"><HTML><HEAD><TITLE></TITLE></HEAD><BODY>MathSEE Members 
 Assembly<br>MathSEE building 20.30<br><br><p>The annual members assembly 
 recapitulates on the events organized by KIT Center MathSEE along with 
 the members and assembles one a year to execute all other formal tasks 
 according to MathSEE foundational documents.</p><br></BODY></HTML>
DESCRIPTION: MathSEE Members Assembly\nMathSEE building 20.30\n\n<p>The
 annual members assembly recapitulates on the events organized by KIT
 Center MathSEE along with the members and assembles one a year to
 execute all other formal tasks according to MathSEE foundational
 documents.</p>\n
DTSTART;TZID=Europe/Berlin:20261123T160000
DTEND;TZID=Europe/Berlin:20261123T173000
LOCATION:MathSEE building 20.30
END:VEVENT
BEGIN:VEVENT
UID: 63102
DTSTAMP:20261030T195923Z
SUMMARY:MathSEED Lecture: Nicola Gnecco
X-ALT-DESC;FMTTYPE=text/html:<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 
 3.2//EN"><HTML><HEAD><TITLE></TITLE></HEAD><BODY>MathSEED Lecture: 
 Nicola Gnecco<br>Mathematics Building 20.30, Room 2.067<br><br><p>Nicola 
 Gnecco&#39;s research aims to develop statistical and machine-learning 
 methods for reliable learning under changing conditions, drawing on 
 causal inference and extreme value theory to improve robustness and 
 understand the limits of extrapolation.</p><br></BODY></HTML>
DESCRIPTION: MathSEED Lecture: Nicola Gnecco\nMathematics Building
 20.30, Room 2.067\n\n<p>Nicola Gnecco's research aims to develop
 statistical and machine-learning methods for reliable learning under
 changing conditions, drawing on causal inference and extreme value
 theory to improve robustness and understand the limits of
 extrapolation.</p>\n
DTSTART;TZID=Europe/Berlin:20261201T154500
DTEND;TZID=Europe/Berlin:20261201T235900
LOCATION:Mathematics Building 20.30, Room 2.067
END:VEVENT
BEGIN:VEVENT
UID: 62208
DTSTAMP:20261030T195923Z
SUMMARY:BAYST Workshop
X-ALT-DESC;FMTTYPE=text/html:<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 
 3.2//EN"><HTML><HEAD><TITLE></TITLE></HEAD><BODY>BAYST 
 Workshop<br>HS93<br><br><p>The <strong>BAYST </strong>workshop aims to 
 bridge recent advances in Bayesian structural learning with applied 
 sciences, fostering scientific discussion and collaboration between 
 theoretical and applied researchers. </p><br><br><p> 
 </p><br><br><p><strong>BAYST </strong>will consist of <strong>20 invited 
 talks</strong> (with discussion) and <strong>2 poster sessions 
 (submissions are open!)</strong> over two and a half days. 
 <strong>Registration is free</strong> for all attendees. Coffee breaks, 
 a welcome reception, and lunches will be provided for presenters (of 
 either a poster or a talk).</p><br><br><p> </p><br><br><p>Moreover, 
 <strong>BAYST </strong>will serve as the kick-off meeting for a 
 potential new section in the International Society of Bayesian Analysis 
 (ISBA) that will be officially proposed to the ISBA Executive Committee 
 after the workshop. The section on Bayesian Structural Learning (BSL) 
 aims to provide an inclusive home for researchers working with 
 high-dimensional or structurally complex data, whether their focus is 
 methodological or applied. Initial officers would be David Dunson, Nadja 
 Klein, Rodney Sparapani, and Deborah Sulem. If you are interested in 
 supporting this initiative, contact us at <a class="XqQF9c" 
 href="mailto:kleinlab@scc.kit.edu" style="color: inherit; 
 text-decoration: none;" target="_blank">kleinlab@scc.kit.edu</a>  to 
 sign our petition.</p><br></BODY></HTML>
DESCRIPTION: BAYST Workshop\nHS93\n\n<p>The <strong>BAYST
 </strong>workshop aims to bridge recent advances in Bayesian structural
 learning with applied sciences, fostering scientific discussion and
 collaboration between theoretical and applied researchers. </p>\n\n<p>
 </p>\n\n<p><strong>BAYST </strong>will consist of <strong>20 invited
 talks</strong> (with discussion) and <strong>2 poster sessions
 (submissions are open!)</strong> over two and a half days.
 <strong>Registration is free</strong> for all attendees. Coffee breaks,
 a welcome reception, and lunches will be provided for presenters (of
 either a poster or a talk).</p>\n\n<p> </p>\n\n<p>Moreover,
 <strong>BAYST </strong>will serve as the kick-off meeting for a
 potential new section in the International Society of Bayesian Analysis
 (ISBA) that will be officially proposed to the ISBA Executive Committee
 after the workshop. The section on Bayesian Structural Learning (BSL)
 aims to provide an inclusive home for researchers working with
 high-dimensional or structurally complex data, whether their focus is
 methodological or applied. Initial officers would be David Dunson, Nadja
 Klein, Rodney Sparapani, and Deborah Sulem. If you are interested in
 supporting this initiative, contact us at <a class="XqQF9c"
 href="mailto:kleinlab@scc.kit.edu" style="color: inherit;
 text-decoration: none;" target="_blank">kleinlab@scc.kit.edu</a>  to
 sign our petition.</p>\n
DTSTART;TZID=Europe/Berlin:20270301
DTEND;TZID=Europe/Berlin:20270301T000000
LOCATION:HS93
END:VEVENT
END:VCALENDAR