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CALSCALE:GREGORIAN
METHOD:PUBLISH
UID:50e8e332-ec30-45d6-8448-20c26be720d2
X-WR-CALNAME:Defence of Rupayan Mallick's thesis (I&S department\, TAD team
 )
X-WR-TIMEZONE:Europe/Paris
BEGIN:VTIMEZONE
TZID:Europe/Paris
TZUNTIL:20251026T010000Z
BEGIN:STANDARD
TZNAME:CET
DTSTART:20221030T030000
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
RDATE:20231029T030000
RDATE:20241027T030000
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TZNAME:CEST
DTSTART:20230326T020000
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
RDATE:20240331T020000
RDATE:20250330T020000
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BEGIN:VEVENT
UID:50e8e332-ec30-45d6-8448-20c26be720d2
DTSTAMP:20260510T224239Z
CLASS:PUBLIC
DESCRIPTION:Rupayan Mallick will present her thesis entitled: 'Explainable 
 Deep Learning with Application to Multimodal Data'.\n
DTSTART;TZID=Europe/Paris:20231020T140000
DTEND;TZID=Europe/Paris:20231020T180000
LOCATION:Amphi LaBRI
ORGANIZER;CN=Jenny Benois-Pineau:mailto:benois-p@labri.fr
SEQUENCE:0
SUMMARY:Defence of Rupayan Mallick's thesis (I&S department\, TAD team)
TRANSP:OPAQUE
END:VEVENT
END:VCALENDAR
