Speaker |
Ozan Öktem |
|---|---|
Affiliation |
Cambridge University/KTH |
Date |
Friday, 01 February 2019 |
Time |
13:00-14:00 |
Location |
Zoom |
Link |
Roberts 421 |
Event series |
DeepMind/ELLIS CSML Seminar Series |
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 show how such reconstruction methods can be integrated with elements of decision making, learning to task adapted reconstruction. It will also survey a recent development in using generative adversarial networks for uncertainty quantification relevant for solving inverse problems. Link to slides: https://people.kth.se/~ozan/UCL_slides.pdf |
Biography |