On the robustness of graph neural diffusion to topology perturbations
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...
| Main Authors: | , , , , |
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| 其他作者: | |
| 格式: | Conference Paper |
| 語言: | English |
| 出版: |
2023
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| 主題: | |
| 在線閱讀: | https://hdl.handle.net/10356/166693 https://proceedings.neurips.cc/ https://nips.cc/Conferences/2022 |