Friday, 30 August 2019, 14:00 at MR11, Centre for Mathematical Sciences, Wilberforce Road, Cambridge – Recent advances in deep learning for tomographic reconstructions have shown great potential to create accurate high quality images with a considerable speed-up compared to classical reconstruction methods. This is especially true for model-based learned (iterative) reconstruction schemes. However, applicability to large scale inverse problems is limited by available memory for …