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SUMMARY:Introductory School "Geometric Statistics" [HIM/HSM Special Topic 
 School]
DTSTART:20260914T070000Z
DTEND:20260918T150000Z
DTSTAMP:20260513T135600Z
UID:indico-event-491@math-events.uni-bonn.de
CONTACT:him-coordination@hcm.uni-bonn.de\;him-contact@hcm.uni-bonn.de
DESCRIPTION:Speakers: Kanami Ueda\, Emma Seggewiss (HCM)\n\nThis HIM Schoo
 l is a week-long event directed at PhD students and recent Postdocs\, whic
 h will take place within the framework of the Dual Trimester Program "Geom
 etric Statistics: theory\, application\, and computation".\nEveryone inter
 ested in participating - regardless of whether financial support is needed
  - must apply\, except for:\n\nPhD students and early-career researchers\,
  who were already invited and have confirmed to be at HIM during the perio
 d of this School. (They are automatically admitted to this event.)\nResear
 chers from the HCM\, in particular\, early-career researchers\, who may jo
 in upon request to the program coordinators Emma Seggewiss and Kanami Ueda
 . (You can find the email addresses below.)\n\nEveryone will be notified i
 n due time about whether participation and partial financial support is po
 ssible. After being selected as participant\, you will be invited to regis
 ter.\nEveryone will be notified in due time about whether participation an
 d partial financial support is possible. After being selected as participa
 nt\, you will be invited to register.\nLecture series by:\n\nFernando Gala
 z-Garcia (Durham University\, UK)\nElton Hsu (Northwestern University\, Ev
 anston\, US)\nXavier Pennec (INRIA\, Université Côte d’Azur\, FR)\nAmy
  Willis (University of Washington\, US)\n\nDescription:\nGeometric statist
 ics focuses on statistical methods that recognize and exploit the geometri
 c structure of data sets\, data objects\, and parameters. Its importance a
 rises from an increasing amount of modern data naturally living on curved\
 , constrained\, or stratified spaces rather than flat Euclidean spaces. No
 table examples of these data objects include shapes\, networks\, covarianc
 e matrices\, trees\, or configuration spaces. On such objects or spaces pa
 rametrizing them\, traditional statistical methods may fail or not apply. 
 New mathematics to deal with these issues often yield surprising results a
 nd high relevance for complex applications in fields such as structural bi
 ology\, physical chemistry\, medical imaging\, robotics\, and forensics.\n
 The Introductory School will provide a set of foundational mini courses de
 signed to equip participants\, especially young researchers and newcomers\
 , with an overview of pertinent background in geometry\, topology\, probab
 ility\, statistics\, and computation specific to statistics and data analy
 sis in settings that are non-Euclidean. In particular\, mini courses will 
 cover foundations of geometric statistics\, asymptotics of Fréchet means 
 on manifolds and stratified spaces\, SDEs on manifolds\, and Alexandrov an
 d RCD spaces. Together\, these mini courses aim to establish a shared scie
 ntific language for participants entering the broader program in geometric
  statistics.\n\nhttps://math-events.uni-bonn.de/event/491/
LOCATION:Poppelsdorfer Allee 45\, 1. EG\, Lecture room (HIM)
URL:https://math-events.uni-bonn.de/event/491/
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