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Diffusion bridge simulation in geometric statistics

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  • UserFrank van der Meulen, Delft University of Technology World_link
  • ClockWednesday 22 May 2019, 14:00-15:00
  • HouseCMS, MR14.

If you have a question about this talk, please contact Alberto J Coca.

Geometric statistics has put forward various models for image deformation. Large deformation diffeomorphic metric mapping provides a framework for deforming a template image to a target image. The transformations are traditionally based on flows defined in terms of Ordinary Differential Equations (ODEs). More recently, stochastic models have been proposed where the ODE is replaced by a stochastic differential equation. Finding a common template image turns out to be closely connected to diffusion bridge simulation in high dimension. For the related but somewhat simpler case of landmark registration, I will discuss how this can be accomplished using guided diffusion processes, as originally defined in Schauer et al. (Bernoulli 23(4), 2917-2950) and further developed in follow-up papers.

This talk is part of the CCIMI Seminars series.

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