BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//jEvents 2.0 for Joomla//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
BEGIN:VTIMEZONE
TZID:America/New_York
BEGIN:STANDARD
DTSTART:20240122T104500
RDATE:20240310T030000
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:America/New_York EST
END:STANDARD
BEGIN:STANDARD
DTSTART:20241103T010000
RDATE:20250309T030000
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:America/New_York EST
END:STANDARD
BEGIN:STANDARD
DTSTART:20251102T010000
RDATE:20260308T030000
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:America/New_York EST
END:STANDARD
BEGIN:STANDARD
DTSTART:20261101T010000
RDATE:20270314T030000
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:America/New_York EST
END:STANDARD
BEGIN:STANDARD
DTSTART:20271107T010000
RDATE:20280312T030000
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:America/New_York EST
END:STANDARD
BEGIN:STANDARD
DTSTART:20281105T010000
RDATE:20290311T030000
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:America/New_York EST
END:STANDARD
BEGIN:DAYLIGHT
DTSTART:20240310T030000
RDATE:20241103T010000
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:America/New_York EDT
END:DAYLIGHT
BEGIN:DAYLIGHT
DTSTART:20250309T030000
RDATE:20251102T010000
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:America/New_York EDT
END:DAYLIGHT
BEGIN:DAYLIGHT
DTSTART:20260308T030000
RDATE:20261101T010000
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:America/New_York EDT
END:DAYLIGHT
BEGIN:DAYLIGHT
DTSTART:20270314T030000
RDATE:20271107T010000
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:America/New_York EDT
END:DAYLIGHT
BEGIN:DAYLIGHT
DTSTART:20280312T030000
RDATE:20281105T010000
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:America/New_York EDT
END:DAYLIGHT
END:VTIMEZONE
BEGIN:VEVENT
UID:cc42999fe0cf8d7a7a4d66ce7ecd8c01
CATEGORIES:Mathematical Physics Seminar
CREATED:20250102T112032
SUMMARY:Webinar: Eric Vanden-Eijnden -  Generative modeling with flows and diffusions
LOCATION:Zoom
DESCRIPTION:<p style="text-align: center;"><strong>Eric Vanden-Eijnden – NYU</strong></
 p><p style="text-align: center;"><strong>&nbsp;</strong></p><p style="text-
 align: center;"><strong>Wednesday,&nbsp;January 22nd ,&nbsp;10:45AM EST</st
 rong></p><p style="text-align: center;"><strong>&nbsp;</strong></p><p style
 ="text-align: center;"><strong>Generative&nbsp;modeling&nbsp;with flows and
  diffusions</strong></p><p style="text-align: center;"><strong>&nbsp;</stro
 ng></p><p>Generative&nbsp;models&nbsp;based on dynamical transport have rec
 ently led to significant advances in unsupervised learning. At mathematical
  level, these&nbsp;models&nbsp;are primarily designed around the constructi
 on of a map between two probability distributions that transform samples fr
 om the first into samples from the second.&nbsp; While these methods were f
 irst introduced in the context of image generation, they have found a wide 
 range of applications, including in scientific computing where they offer i
 nteresting ways to reconsider complex problems once thought intractable bec
 ause of the curse of dimensionality. In this talk, I will discuss the mathe
 matical underpinning of&nbsp;generative&nbsp;models&nbsp;based on flows and
  diffusions, and show how a better understanding of their inner workings ca
 n help improve their design. These results indicate how to structure the tr
 ansport to best reach complex target distributions while maintaining comput
 ational efficiency, both at learning and sampling stages.&nbsp; I will also
  discuss applications of&nbsp;generative&nbsp;AI in scientific computing, i
 n particular in the context of Monte Carlo sampling, with applications to t
 he statistical mechanics and Bayesian inference, as well as probabilistic f
 orecasting, with application to fluid dynamics and atmosphere/ocean science
 .</p>
DTSTAMP:20260826T061102
DTSTART;TZID=America/New_York:20250122T104500
DTEND;TZID=America/New_York:20250122T120000
SEQUENCE:0
TRANSP:OPAQUE
END:VEVENT
END:VCALENDAR