On the robustness of graph neural diffusion to topology perturbations

• المؤلفون الرئيسيون: Song, Yang, Kang, Qiyu, Wang, Sijie, Zhao, Kai, Tay, Wee Peng
• مؤلفون آخرون: School of Electrical and Electronic Engineering
• التنسيق: Conference or Workshop Item
• اللغة: English
• منشور في: 2023
• الموضوعات: Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence; Graph Neural Networks; Deep Learning
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/166693; https://proceedings.neurips.cc/; https://nips.cc/Conferences/2022
• المؤسسة: Nanyang Technological University

Neural diffusion on graphs is a novel class of graph neural networks that has attracted increasing attention recently. The capability of graph neural partial differential equations (PDEs) in addressing common hurdles of graph neural networks (GNNs), such as the problems of over-smoothing and bottlen...