Learning How to Propagate Messages in Graph Neural Networks

Learning How to Propagate Messages in Graph Neural Networks

1 October 2023

ArXiv (abs)PDF HTML

Papers citing "Learning How to Propagate Messages in Graph Neural Networks"

11 / 11 papers shown

Title
Mitigating Degree Bias Adaptively with Hard-to-Learn Nodes in Graph Contrastive Learning Jingyu Hu Hongbo Bo Jun Hong Xiaowei Liu Weiru Liu 117 0 0 05 Jun 2025
Early-Exit Graph Neural Networks Andrea Giuseppe Di Francesco Maria Sofia Bucarelli F. M. Nardini R. Perego Nicola Tonellotto Fabrizio Silvestri 146 0 0 23 May 2025
Subgraph Federated Learning for Local Generalization Sungwon Kim Yoonho Lee Yunhak Oh Namkyeong Lee Sukwon Yun Junseok Lee Sein Kim Carl Yang Chanyoung Park FedML OOD 157 3 0 06 Mar 2025
CONTINUUM: Detecting APT Attacks through Spatial-Temporal Graph Neural Networks Atmane Ayoub Mansour Bahar Kamel Soaid Ferrahi Mohamed-Lamine Messai H. Seba Karima Amrouche 92 0 0 08 Jan 2025
AnyGraph: Graph Foundation Model in the Wild Lianghao Xia Chao Huang OOD 113 18 0 20 Aug 2024
Learning to Reweight for Graph Neural Network Zhengyu Chen Teng Xiao Kun Kuang Zheqi Lv Min Zhang Jinluan Yang Chengqiang Lu Hongxia Yang Leilei Gan OOD 95 1 0 19 Dec 2023
Faithful and Consistent Graph Neural Network Explanations with Rationale Alignment Tianxiang Zhao Dongsheng Luo Xiang Zhang Suhang Wang 134 7 0 07 Jan 2023
Decoupled Self-supervised Learning for Non-Homophilous Graphs Teng Xiao Zhengyu Chen Zhimeng Guo Zeyang Zhuang Suhang Wang BDL SSL 97 18 0 07 Jun 2022
Towards Faithful and Consistent Explanations for Graph Neural Networks Tianxiang Zhao Dongsheng Luo Xiang Zhang Suhang Wang FAtt 145 20 0 27 May 2022
A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability Enyan Dai Tianxiang Zhao Huaisheng Zhu Jun Xu Zhimeng Guo Hui Liu Jiliang Tang Suhang Wang 114 144 0 18 Apr 2022
Exploring Edge Disentanglement for Node Classification Tianxiang Zhao Xiang Zhang Suhang Wang 108 35 0 23 Feb 2022