Optimizing Polynomial Graph Filters: A Novel Adaptive Krylov Subspace Approach

12 March 2024

Papers citing "Optimizing Polynomial Graph Filters: A Novel Adaptive Krylov Subspace Approach"

5 / 5 papers shown

Title
GCON: Differentially Private Graph Convolutional Network via Objective Perturbation Jianxin Wei Yizheng Zhu Xiaokui Xiao Ergute Bao Yin Yang Kuntai Cai Beng Chin Ooi AAML 27 0 0 06 Jul 2024
How Universal Polynomial Bases Enhance Spectral Graph Neural Networks: Heterophily, Over-smoothing, and Over-squashing Keke Huang Yu Guang Wang Ming Li Pietro Lió 35 17 0 21 May 2024
How Powerful are Spectral Graph Neural Networks Xiyuan Wang Muhan Zhang 70 178 0 23 May 2022
Geom-GCN: Geometric Graph Convolutional Networks Hongbin Pei Bingzhen Wei Kevin Chen-Chuan Chang Yu Lei Bo Yang GNN 169 1,072 0 13 Feb 2020
Geometric deep learning: going beyond Euclidean data M. Bronstein Joan Bruna Yann LeCun Arthur Szlam P. Vandergheynst GNN 231 3,230 0 24 Nov 2016