AI Seminar: Bayesian inversion for tomography through machine learning

Speaker

Ozan Ötkem from KTH Sweden, Strategic Coordinator for the Center for Applied and Industrial Mathematics (CIAM).

Title

Bayesian inversion for tomography through machine learning

Abstract

The talk will outline recent approaches for using (deep) convolutional neural networks to solve a wide range of inverse problems, such as tomographic image reconstruction. Emphasis is on learned iterative schemes that use a neural network architecture for reconstruction that includes physics based models for how data is generated. The talk will also discuss recent developments in using generative adversarial networks for uncertainty quantification in inverse problems.