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SUMMARY:Collective dynamics in the social and data sciences - Marie-Theres
 e Wolfram (Warwick)
DTSTART:20221128T150000Z
DTEND:20221128T160000Z
UID:TALK192866@talks.cam.ac.uk
CONTACT:Matthew Colbrook
DESCRIPTION:Collective dynamics can be observed in many situations in our 
 daily lives\, for example the motion of bird flocks\, the formation of dir
 ectional lanes in pedestrian flows or opinion dynamics on social media. In
  all these examples interactions of close individuals lead to the formatio
 n of complex phenomena in the entire population.\n\nIn this talk I will di
 scuss different mathematical models to describe large interacting particle
  systems. I will then focus on the corresponding macroscopic equations\, w
 hich describe the evolution of the entire population. These equations ofte
 n have a gradient flow structure\, which can be used to analyse the large 
 time behaviour. I will discuss the structure of these equilibrium solution
 s and how they relate to the observed complex behaviour. Finally\, I will 
 discuss the application of these ideas in the context of data science\, in
  particular Bayesian inversion.
LOCATION:Centre for Mathematical Sciences\, MR10
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