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SUMMARY:Bayesian inversion for tomography through machine learning - Ozan 
 Öktem (KTH Stockholm and Alan Turing Institute)
DTSTART:20190307T150000Z
DTEND:20190307T160000Z
UID:TALK119608@talks.cam.ac.uk
CONTACT:Carola-Bibiane Schoenlieb
DESCRIPTION:The talk will outline recent approaches for using (deep) convo
 lutional neural networks to solve a wide range of inverse problems\, such 
 as tomographic image reconstruction. Emphasis is on learned iterative sche
 mes that use a neural network architecture for reconstruction that include
 s physics based models for how data is generated. The talk will also discu
 ss recent developments in using generative adversarial networks for uncert
 ainty quantification in inverse problems.
LOCATION:MR 14
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