2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information

2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information
Login Paper Search My Schedule Paper Index Help

My ICASSP 2021 Schedule

Note: Your custom schedule will not be saved unless you create a new account or login to an existing account.
  1. Create a login based on your email (takes less than one minute)
  2. Perform 'Paper Search'
  3. Select papers that you desire to save in your personalized schedule
  4. Click on 'My Schedule' to see the current list of selected papers
  5. Click on 'Printable Version' to create a separate window suitable for printing (the header and menu will appear, but will not actually print)
Click on the icon to view the manuscript on IEEE XPlore in the IEEE ICASSP 2021 Open Preview.

Clicking on the Add button next to a paper title will add that paper to your custom schedule.
Clicking on the Remove button next to a paper will remove that paper from your custom schedule.

SS-2: Deep Learning Methods for Solving Linear Inverse Problems

Session Type: Poster
Time: Tuesday, 8 June, 14:00 - 14:45
Location: Gather.Town
Session Chairs: Wei Chen, Beijing Jiaotong University, David Wipf, Amazon AI Research Lab and Miguel Rodrigues, University College London
 
   SS-2.1: MODEL-INSPIRED DEEP LEARNING FOR LIGHT-FIELD MICROSCOPY WITH APPLICATION TO NEURON LOCALIZATION
         Pingfan Song; Imperial College London
         Herman Verinaz Jadan; Imperial College London
         Carmel Howe; Imperial College London
         Peter Quicke; Imperial College London
         Amanda Foust; Imperial College London
         Pier Luigi Dragotti; Imperial College London
 
   SS-2.2: TIME-VARYING GRAPH SIGNAL INPAINTING VIA UNROLLING NETWORKS
         Siheng Chen; Mitsubishi Electric Research Laboratories (MERL)
         Yonina C. Eldar; Weizmann Institute of Science
 
   SS-2.3: DEEP LEARNING FOR LINEAR INVERSE PROBLEMS USING THE PLUG-AND-PLAY PRIORS FRAMEWORK
         Wei Chen; Beijing Jiaotong University
         David Wipf; Amazon AI Research Lab
         Miguel R.D. Rodrigues; University College London
 
   SS-2.4: A PLUG-AND-PLAY DEEP IMAGE PRIOR
         Zhaodong Sun; Ecole Polytechnique Fédérale de Lausanne (EPFL)
         Fabian Latorre; Ecole Polytechnique Fédérale de Lausanne (EPFL)
         Thomas Sanchez; Ecole Polytechnique Fédérale de Lausanne (EPFL)
         Volkan Cevher; Ecole Polytechnique Fédérale de Lausanne (EPFL)
 
   SS-2.5: MRI IMAGE RECOVERY USING DAMPED DENOISING VECTOR AMP
         Subrata Sarkar; Ohio State
         Rizwan Ahmad; Ohio State
         Philip Schniter; Ohio State
 
   SS-2.6: OVERCOMING MEASUREMENT INCONSISTENCY IN DEEP LEARNING FOR LINEAR INVERSE PROBLEMS: APPLICATIONS IN MEDICAL IMAGING
         Marija Vella; Heriot-Watt University
         João F. C. Mota; Heriot-Watt University