E-9: Sensing and Learning for Inverse Problems (invited) |
Session Type: Virtual |
Time: Tuesday, November 1, 11:00 - 12:00 |
Location: Virtual G |
Virtual Session: Attend on Virtual Platform |
E-9.1: One-dimensional Deep Image Prior for Time Series Inverse Problems |
Sriram Ravula; The University of Texas at Austin |
Alexandros Dimakis; The University of Texas at Austin |
E-9.2: Exact recovery of coordinate-based neural network image representations from Fourier samples |
Gregory Ongie; Marquette University |
E-9.3: Exploring the Geometry of Generative Priors with Applications in Cellular MRI |
Sina Shahsavari; University of California, San Diego |
Jiawen Chen; University of California, San Diego |
Piya Pal; University of California, San Diego |
E-9.4: Universality of Approximate Message Passing with Semi-Random Matrices |
Yue Lu; Harvard University |