AdaFGL: A New Paradigm for Federated Node Classification with Topology
Heterogeneity

AdaFGL: A New Paradigm for Federated Node Classification with Topology Heterogeneity

22 January 2024

Zhengyu Wu

Papers citing "AdaFGL: A New Paradigm for Federated Node Classification with Topology Heterogeneity"

6 / 6 papers shown

Title
Rethinking Federated Graph Learning: A Data Condensation Perspective Hao Zhang Xunkai Li Y. X. Zhu Lianglin Hu FedML DD AI4CE 47 0 0 05 May 2025
Label-Wise Graph Convolutional Network for Heterophilic Graphs Enyan Dai Shijie Zhou Zhimeng Guo Suhang Wang 35 18 0 15 Oct 2021
Towards Personalized Federated Learning A. Tan Han Yu Li-zhen Cui Qiang Yang FedML AI4CE 180 832 0 01 Mar 2021
Line Graph Neural Networks for Link Prediction Lei Cai Jundong Li Jie Wang Shuiwang Ji GNN 130 194 0 20 Oct 2020
Geom-GCN: Geometric Graph Convolutional Networks Hongbin Pei Bingzhen Wei Kevin Chen-Chuan Chang Yu Lei Bo Yang GNN 167 1,058 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 226 1,935 0 09 Jun 2018