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UID:83@atst.osups.universite-paris-saclay.fr
DTSTART;TZID=America/New_York;VALUE=DATE:20251013
DTEND;TZID=America/New_York;VALUE=DATE:20251018
DTSTAMP:20250428T214147Z
URL:https://atst.osups.universite-paris-saclay.fr/calendrier/lmag2025/
SUMMARY:Workshop on Machine Learning\, Data Mining\, and Data Assimilation 
 in Geospace
DESCRIPTION:The 3rd meeting on Machine Learning\, Data Mining\, and Data As
 similation in Geospace (LMAG2025)\, will take place from 13-17 October 202
 5 at JHU/APL (USA). This will be primarily in-person\, with limited remote
  access for those with strong constraints. As before\, this will be an inf
 ormal\, community-driven workshop. There is no registration fee\, and the 
 format will emphasize open discussion and focus on interaction and collabo
 rative exploration.\n\nWorkshop details (TBD based on number of participan
 ts):\n\n 	Science topics: See website\; we welcome suggestions for updatin
 g these\n 	Preliminary Format: ~20 minute talks + short Q&amp\;A\; a longe
 r discussion session at the end of each day\n 	Audience: ~50-75 participan
 ts expected from magnetospheric\, ionospheric\, astrophysics\, planetary\,
  and heliospheric communities\, along with data and computer science exper
 ts.\n\n(Transmis par Thierry Dudok de Wit)
CATEGORIES:Workshops, conferences and schools
LOCATION:JHU/APL\, Johns Hopkins University Applied Physics Laboratory\, La
 urel\, Maryland\, États-Unis
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Johns Hopkins University Ap
 plied Physics Laboratory\, Laurel\, Maryland\, États-Unis;X-APPLE-RADIUS=
 100;X-TITLE=JHU/APL:geo:0,0
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