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Beyond Over-smoothing: Uncovering the Trainability Challenges in Deep Graph Neural Networks

Beyond Over-smoothing: Uncovering the Trainability Challenges in Deep Graph Neural Networks

Jie Peng
Runlin Lei
Zhewei Wei
ArXiv (abs)PDFHTML

Papers citing "Beyond Over-smoothing: Uncovering the Trainability Challenges in Deep Graph Neural Networks"

4 / 4 papers shown
Title
Efficient Mixed Precision Quantization in Graph Neural Networks
Efficient Mixed Precision Quantization in Graph Neural Networks
Samir Moustafa
Nils M. Kriege
Wilfried Gansterer
GNNMQ
71
0
0
14 May 2025
ScaleGNN: Towards Scalable Graph Neural Networks via Adaptive High-order Neighboring Feature Fusion
ScaleGNN: Towards Scalable Graph Neural Networks via Adaptive High-order Neighboring Feature Fusion
Xiang Li
Haobing Liu
Jianpeng Qi
Yuan Cao
Guoqing Chao
Yanwei Yu
Junyu Dong
Yanwei Yu
GNN
104
0
0
22 Apr 2025
A Signed Graph Approach to Understanding and Mitigating Oversmoothing in GNNs
A Signed Graph Approach to Understanding and Mitigating Oversmoothing in GNNs
Jiaqi Wang
Xinyi Wu
James Cheng
Yifei Wang
19
0
0
17 Feb 2025
Geometric Machine Learning on EEG Signals
Geometric Machine Learning on EEG Signals
Benjamin J. Choi
113
1
0
07 Feb 2025

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