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SUMMARY:Stefan Sommer (Copenhagen)
DTSTART:20210617T134500Z
DTEND:20210617T143000Z
DTSTAMP:20260423T005846Z
UID:YRbGSA/12
DESCRIPTION:Title: <a href="https://researchseminars.org/talk/YRbGSA/12/">
 Sub-Riemannian geometry in probabilistic geometric statistics</a>\nby Stef
 an Sommer (Copenhagen) as part of Young Researchers between Geometry and S
 tochastic Analysis 2021\n\n\nAbstract\nGeometric statistics\, the statisti
 cal analysis of manifold and Lie group valued data\, can be approached fro
 m a probabilistic viewpoint where families of parametric probability distr
 ibutions are fitted to data.\n\nThis likelihood-based approach gives one w
 ay to generalize Euclidean statistical procedures to the non-linear manifo
 ld context. Stochastic processes here play an important role in providing 
 geometrically natural ways of defining probability distributions. In the t
 alk\, I will discuss such constructions and how they lead to new geometric
  evolution equations for the most probable paths to observed data. In part
 icular\, we will see how such paths for an anisotropically scaled Brownian
  motion arise as geodesics of a sub-Riemannian metric on the frame bundle 
 of the manifold.\n
LOCATION:https://researchseminars.org/talk/YRbGSA/12/
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