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Distinguishing Neighborhood Representations Through Reverse Process of GNNs for Heterophilic Graphs
Graph Neural Network (GNN) resembles the diffusion process, leading to the over-smoothing of learned representations when stacking many layers.
EPIC: Graph Augmentation with Edit Path Interpolation via Learnable Cost
Graph-based models have become increasingly important in various domains, but the limited size and diversity of existing graph datasets often limit their performance.
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