Optimisation and Deep learning for computational imaging in radioastronomy - unveiling Star Wars hidden facts and misconceptions

Endowing advanced imaging instruments such as telescopes and medical scanners with an acute vision that enables them to probe the Universe or human body with precision is a complex mathematical endeavour. It requires solving challenging inverse problems for image formation from observed data. In this talk, we dive into this field of computational imaging, and its specific application in radio astronomy, where algorithms are currently facing a multi-faceted challenge for the robust reconstruction of images at extreme resolution and dynamic range, and from extreme data volumes. We will be discussing advanced algorithms at the interface of optimisation and deep learning theories, from SARA, an optimisation algorithm propelled by handcrafted priors, to AIRI, plug-and-play algorithm relying on learned denoisers, and a newborn network series approach R2D2. Most importantly, we will also take few seconds to unveil Star Wars hidden facts and misconceptions.

The talk will be followed by a Christmas gathering: 16.40 - 17.00 Crush area in from of EM 2.44