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SUMMARY:Isabel Haasler (Uppsala University)
DTSTART:20250526T111500Z
DTEND:20250526T120000Z
DTSTAMP:20260417T004450Z
UID:cam/70
DESCRIPTION:Title: <a href="https://researchseminars.org/talk/cam/70/">Sys
 tem identification in large populations using optimal transport</a>\nby Is
 abel Haasler (Uppsala University) as part of CAM seminar\n\nLecture held i
 n MV:L14.\n\nAbstract\nIdentifying the dynamics of individual agents from 
 aggregate\, population-level data is a key challenge in many applications\
 , ranging from biology to crowd dynamics and traffic systems. In recent ye
 ars\, optimal transport theory has emerged as a powerful tool for modeling
  large populations of agents\, as it bridges a population-level viewpoint 
 with an agent-level viewpoint.\n\nIn this talk\, I will show how optimal t
 ransport can be used to identify agent dynamics from snapshot observations
  of the full population. This idea extends even to heterogeneous populatio
 ns\, where the observed data results from a superposition of multiple subp
 opulations\, each governed by distinct dynamics. In this case\, our method
  simultaneously separates the population into ensembles and identifies eac
 h ensemble’s governing system\, using only aggregate snapshot observatio
 ns.\n
LOCATION:https://researchseminars.org/talk/cam/70/
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