Bayesian inversion for tomography through machine learning

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• Ozan Öktem (KTH Stockholm and Alan Turing Institute)
• Thursday 07 March 2019, 15:00-16:00
• MR 14.

If you have a question about this talk, please contact Carola-Bibiane Schoenlieb.

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.

This talk is part of the Applied and Computational Analysis series.

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