On Bayesian Models with Networks for Reconstruction and Detection
Institute for Pure & Applied Mathematics (IPAM) via YouTube
Overview
Syllabus
Intro
Outline
Acknowledgements
Examples: Image enhancement
Posterior distribution
Cartoon representation
Why use generative models for analyzing images?
Principal component analysis
Variational auto-encoders
MRI acquisition
Bayesian model for image reconstruction
MAP estimation with network prior
Advantage of generative modeling: decoupling
A distinction in the concept of "prior"
Unsupervised outlier detection
Restoration for outlier detection
Experimental details
ROC curves
Taught by
Institute for Pure & Applied Mathematics (IPAM)