DeLTA Seminar by Stefan Sommer
On 9 May, the DeLTA Lab from the Department of Computer Science, UCPH, holds a seminar titled 'Stochastic shape analysis and probabilistic geometric statistics' by Stefan Sommer.
Speaker
Stefan Sommer, Professor in the IMAGE section at the Department of Computer Science.
Title
Stochastic shape analysis and probabilistic geometric statistics
Abstract
Analysis and statistics of shape variation observed in e.g. medical imaging and biology can be formulated in a geometric framework with geodesics modelling transitions between shapes. The talk will discuss this setting along with extensions of the smooth geodesic models to account for noise and uncertainty. In the stochastic case, shape matching algorithms take the form of stochastic bridge simulation schemes which also provide approximations of the transition density of the underlying stochastic shape processes. I will connect these ideas to geometric statistics, the statistical analysis of general manifold valued data, particularly to the diffusion mean.
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DeLTA is a research group affiliated with the Department of Computer Science at the University of Copenhagen studying diverse aspects of Machine Learning Theory and its applications, including, but not limited to Reinforcement Learning, Online Learning and Bandits, PAC-Bayesian analysis