2020 IEEE International Symposium
on Information Theory
21-26 June 2020 • Los Angeles, California, USA
L.8: Learning and Message-Passing | |
| Session Type: Lecture | |
| Track: Statistics and Learning Theory | |
| Virtual Session: View on Virtual Platform | |
| Session Chair: Hans-Andrea Loeliger, ETH Zurich | |
| L.8.1: The Power of Graph Convolutional Networks to Distinguish Random Graph Models | |
| Click here to download the manuscript | |
| Click here to view the Virtual Presentation | |
| Abram Magner; University at Albany, State University of New York | |
| Mayank Baranwal; University of Michigan | |
| Alfred O. Hero; University of Michigan | |
| L.8.2: Exponentially Fast Concentration of Vector Approximate Message Passing to its State Evolution | |
| Click here to download the manuscript | |
| Click here to view the Virtual Presentation | |
| Collin Cademartori; Columbia University | |
| Cynthia Rush; Columbia University | |
| L.8.3: Online Message Passing-based Inference in the Hierarchical Gaussian Filter | |
| Click here to download the manuscript | |
| Click here to view the Virtual Presentation | |
| Ismail Senoz; Eindhoven University of Technology | |
| Bert de Vries; Eindhoven University of Technology | |
| L.8.4: Data-Driven Factor Graphs for Deep Symbol Detection | |
| Click here to download the manuscript | |
| Click here to view the Virtual Presentation | |
| Nir Shlezinger; Weizmann Institute of Science | |
| Nariman Farsad; Stanford | |
| Yonina Eldar; Weizmann Institute of Science | |
| Andrea Goldsmith; Stanford | |
Plan Ahead
2021 IEEE International Symposium on Information Theory
11-16 July 2021 | Melbourne, Victoria, Australia
