BEGIN:VCALENDAR
VERSION:2.0
METHOD:PUBLISH
CALSCALE:GREGORIAN
PRODID:-//WordPress - MECv6.5.6//EN
X-ORIGINAL-URL:https://cmc.deusto.eus/
X-WR-CALNAME:cmc.deusto.eus
X-WR-CALDESC:DeustoCCM - Chair of Computational Mathematics at University of Deusto
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-PUBLISHED-TTL:PT1H
X-MS-OLK-FORCEINSPECTOROPEN:TRUE
BEGIN:VEVENT
CLASS:PUBLIC
UID:MEC-f455d7705320f70db3783e0358111fcf@cmc.deusto.eus
DTSTART:20211208T150000Z
DTEND:20211208T160000Z
DTSTAMP:20251031T223700Z
CREATED:20251031
LAST-MODIFIED:20251031
PRIORITY:5
TRANSP:OPAQUE
SUMMARY:Neural network and partial differential equations
DESCRIPTION:Speaker: Prof. Dr. Lexing Ying\nAffiliation: Stanford University, Department of Mathematics and ICME, Institute for Computational and Mathematical Engineering (USA)\nOrganized by: FAU DCN-AvH, Chair for Dynamics, Control and Numerics – Alexander von Humboldt Professorship at FAU Erlangen-Nürnberg (Germany)\nZoom meeting link\nMeeting ID: 627 2528 2026 | PIN: 138876\nAbstract. In this talk, we will discuss recent interaction between neural networks and partial differential equations. In one direction, neural networks have brought some recent successes in solving partial differential equation problems. In the other direction, partial differential equations offer new perspectives on architecture design, optimization, and generative modeling.\nThis event on LinkedIn\n
URL:https://cmc.deusto.eus/events-calendar/neural-network-and-partial-differential-equations/
ORGANIZER;CN=FAU DCN-AvH:MAILTO:
CATEGORIES:FAU DCN-AvH Seminar
LOCATION:FAU DCN-AvH
ATTACH;FMTTYPE=image/png:https://cmc.deusto.eus/wp-content/uploads/FAUDCNSeminar-lYing-08dic2021.png
END:VEVENT
END:VCALENDAR