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BEGIN:VCALENDAR VERSION:2.0 PRODID:-//Penn Engineering Events - ECPv6.18.0//NONSGML v1.0//EN CALSCALE:GREGORIAN METHOD:PUBLISH X-WR-CALNAME:Penn Engineering Events X-ORIGINAL-URL:https://seasevents.nmsdev7.com X-WR-CALDESC:Events for Penn Engineering Events REFRESH-INTERVAL;VALUE=DURATION:PT1H X-Robots-Tag:noindex X-PUBLISHED-TTL:PT1H BEGIN:VTIMEZONE TZID:America/New_York BEGIN:DAYLIGHT TZOFFSETFROM:-0500 TZOFFSETTO:-0400 TZNAME:EDT DTSTART:20190310T070000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0400 TZOFFSETTO:-0500 TZNAME:EST DTSTART:20191103T060000 END:STANDARD BEGIN:DAYLIGHT TZOFFSETFROM:-0500 TZOFFSETTO:-0400 TZNAME:EDT DTSTART:20200308T070000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0400 TZOFFSETTO:-0500 TZNAME:EST DTSTART:20201101T060000 END:STANDARD BEGIN:DAYLIGHT TZOFFSETFROM:-0500 TZOFFSETTO:-0400 TZNAME:EDT DTSTART:20210314T070000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0400 TZOFFSETTO:-0500 TZNAME:EST DTSTART:20211107T060000 END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTART;TZID=America/New_York:20201016T100000 DTEND;TZID=America/New_York:20201016T110000 DTSTAMP:20200924T194101Z CREATED:20200924T194101Z LAST-MODIFIED:20200924T194101Z UID:3488-1602842400-1602846000@seasevents.nmsdev7.com SUMMARY:SIG Seminar: "Uncertainty-Driven Geometry Reconstruction and Understanding" DESCRIPTION:Choosing suitable data representations is one of the most critical topics when installing machine learning on 3D data. This talk discusses several recent works on utilizing uncertainty as a lens to develop suitable data representations and formulations for geometry reconstruction and understanding. We will discuss both theoretical results and applications in multi-scan registration\, pose estimation\, and scene understanding. URL:https://seasevents.nmsdev7.com/event/sig-seminar-uncertainty-driven-geometry-reconstruction-and-understanding/ LOCATION:Zoom – Email CIS for link\, cherylh@cis.upenn.edu ORGANIZER;CN="Computer and Information Science":MAILTO:cherylh@cis.upenn.edu END:VEVENT END:VCALENDAR