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cs.LG2024★ 1 cited
Taming Gradient Oversmoothing and Expansion in Graph Neural Networks
MoonJeong Park, Dongwoo Kim
Oversmoothing has been claimed as a primary bottleneck for multi-layered graph neural networks (GNNs). Multiple analyses have examined how and why oversmoothing occurs. However, no…
cs.LG2024
Posterior Label Smoothing for Node Classification
Jaeseung Heo, Moonjeong Park, Dongwoo Kim
Label smoothing is a widely studied regularization technique in machine learning. However, its potential for node classification in graph-structured data, spanning homophilic to he…
cs.SI2024
Mitigating Oversmoothing Through Reverse Process of GNNs for Heterophilic Graphs
MoonJeong Park, Jaeseung Heo, Dongwoo Kim
Graph Neural Network (GNN) resembles the diffusion process, leading to the over-smoothing of learned representations when stacking many layers. Hence, the reverse process of messag…