Beyond Low-frequency Information in Graph Convolutional Networks

4 January 2021

Papers citing "Beyond Low-frequency Information in Graph Convolutional Networks"

9 / 9 papers shown

Title
Addressing Noise and Stochasticity in Fraud Detection for Service Networks Wenxin Zhang Ding Xu Xi Xuan Lei Jiang Guangzhen Yao Renda Han Xiangxiang Lang Cuicui Luo 6 0 0 02 May 2025
Understanding GNNs and Homophily in Dynamic Node Classification Michael Ito Danai Koutra Jenna Wiens 32 1 0 29 Apr 2025
Learning Laplacian Positional Encodings for Heterophilous Graphs Michael Ito Jiong Zhu Dexiong Chen Danai Koutra Jenna Wiens 36 1 0 29 Apr 2025
FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Zihan Chen Xingbo Fu Yushun Dong Jundong Li Cong Shen FedML 44 0 0 29 Apr 2025
Hierarchical Uncertainty-Aware Graph Neural Network Yoonhyuk Choi Jiho Choi Taewook Ko Chong-Kwon Kim 31 46 0 28 Apr 2025
Dual-channel Heterophilic Message Passing for Graph Fraud Detection W. Zhang Jingxing Zhong Guangzhen Yao Renda Han Xiaojian Lin Zeyu Zhang Cuicui Luo 18 0 0 19 Apr 2025
Geom-GCN: Geometric Graph Convolutional Networks Hongbin Pei Bingzhen Wei Kevin Chen-Chuan Chang Yu Lei Bo Yang GNN 154 874 0 13 Feb 2020
Multi-scale Attributed Node Embedding Benedek Rozemberczki Carl Allen Rik Sarkar GNN 128 682 0 28 Sep 2019
Geometric deep learning on graphs and manifolds using mixture model CNNs Federico Monti Davide Boscaini Jonathan Masci Emanuele Rodolà Jan Svoboda M. Bronstein GNN 212 1,728 0 25 Nov 2016