How does Heterophily Impact the Robustness of Graph Neural Networks? Theoretical Connections and Practical Implications

14 June 2021

Papers citing "How does Heterophily Impact the Robustness of Graph Neural Networks? Theoretical Connections and Practical Implications"

10 / 10 papers shown

Title
SpecSphere: Dual-Pass Spectral-Spatial Graph Neural Networks with Certified Robustness Y. Choi Chong-Kwon Kim 29 0 0 13 May 2025
MADE: Graph Backdoor Defense with Masked Unlearning Xiao Lin amd Mingjie Li Mingjie Li Yisen Wang AAML 95 1 0 03 Jan 2025
Graph Neural Convection-Diffusion with Heterophily Kai Zhao Qiyu Kang Yang Song Rui She Sijie Wang Wee Peng Tay 26 27 0 26 May 2023
On Graph Neural Network Fairness in the Presence of Heterophilous Neighborhoods Donald Loveland Jiong Zhu Mark Heimann Benjamin Fish Michael T. Schaub Danai Koutra 27 6 0 10 Jul 2022
AdaGNN: Graph Neural Networks with Adaptive Frequency Response Filter Yushun Dong Kaize Ding B. Jalaeian Shuiwang Ji Jundong Li 64 60 0 26 Apr 2021
Two Sides of the Same Coin: Heterophily and Oversmoothing in Graph Convolutional Neural Networks Yujun Yan Milad Hashemi Kevin Swersky Yaoqing Yang Danai Koutra 36 247 0 12 Feb 2021
Beyond Low-frequency Information in Graph Convolutional Networks Deyu Bo Xiao Wang C. Shi Huawei Shen GNN 94 561 0 04 Jan 2021
Geom-GCN: Geometric Graph Convolutional Networks Hongbin Pei Bingzhen Wei Kevin Chen-Chuan Chang Yu Lei Bo Yang GNN 169 1,078 0 13 Feb 2020
Representation Learning on Graphs with Jumping Knowledge Networks Keyulu Xu Chengtao Li Yonglong Tian Tomohiro Sonobe Ken-ichi Kawarabayashi Stefanie Jegelka GNN 267 1,945 0 09 Jun 2018
Geometric deep learning: going beyond Euclidean data M. Bronstein Joan Bruna Yann LeCun Arthur Szlam P. Vandergheynst GNN 253 3,236 0 24 Nov 2016