| Paper ID | SS-L3.4 | ||
| Paper Title | TOWARDS AN EFFICIENT AND GENERAL FRAMEWORK OF ROBUST TRAINING FOR GRAPH NEURAL NETWORKS | ||
| Authors | Kaidi Xu, Northeastern University, United States; Sijia Liu, Pin-Yu Chen, IBM Research, United States; Mengshu Sun, Northeastern University, United States; Caiwen Ding, University of Connecticut, United States; Bhavya Kailkhura, Lawrence Livermore National Laboratory, United States; Xue Lin, Northeastern University, United States | ||
| Session | SS-L3: A Signal-Processing View of Graph Neural Networks | ||
| Location | On-Demand | ||
| Session Time: | Tuesday, 05 May, 11:30 - 13:30 | ||
| Presentation Time: | Tuesday, 05 May, 12:30 - 12:50 | ||
| Presentation | Lecture | ||
| Topic | Special Sessions: A Signal-Processing View of Graph Neural Networks | ||
| IEEE Xplore Open Preview | Click here to view in IEEE Xplore | ||
| Virtual Presentation | Click here to watch in the Virtual Conference | ||