Speaker
Jay Newby
(University of Alberta)
Description
I will discuss the use of diffusion models for particle tracking microscopy images. The goal is to have a fully integrated generative model that connects stochastic models of particle motion to microscopy image data. Unfortunately, the observation likelihood function is too complex to explicitly model, and we do not know this function. Learning the likelihood function from a suitably large image set is the primary purpose of so-called diffusion models. We discuss the application of these neural network models for evaluating the log likelihood of image sets given particle positions.
Author
Jay Newby
(University of Alberta)
