Signal Recovery with Generative Priors - SIAM-IS Virtual Seminar

Explore the cutting-edge developments in image recovery techniques during this one-hour virtual seminar talk from the 29th Imaging & Inverse Problems (IMAGINE) OneWorld SIAM-IS series. Delve into the world of signal recovery with generative priors as presented by speaker Paul Hand. Learn about the importance of recovering images from limited measurements in imaging problems and the role of image priors in this process. Discover how neural networks and machine learning advancements have revolutionized image priors for inverse problems in imaging. Gain insights into rigorous recovery guarantees for compressed sensing and other inverse problems, as well as efficient algorithms for phase retrieval from generic measurements. Examine the strengths, weaknesses, and future opportunities of neural networks and generative models as image priors. This talk covers collaborative work with various researchers and provides a comprehensive overview of the latest developments in the field of imaging and inverse problems.