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cs.LG2026
Unified Multi-Domain Graph Pre-training for Homogeneous and Heterogeneous Graphs via Domain-Specific Expert Encoding
Chundong Liang, Yongqi Huang, Dongxiao He +4
Graph pre-training has achieved remarkable success in recent years, delivering transferable representations for downstream adaptation. However, most existing methods are designed f…
cs.LG2022
TrustGNN: Graph Neural Network based Trust Evaluation via Learnable Propagative and Composable Nature
Cuiying Huo, Di Jin, Chundong Liang +3
Trust evaluation is critical for many applications such as cyber security, social communication and recommender systems. Users and trust relationships among them can be seen as a g…
cs.LG2021
Block Modeling-Guided Graph Convolutional Neural Networks
Dongxiao He, Chundong Liang, Huixin Liu +3
Graph Convolutional Network (GCN) has shown remarkable potential of exploring graph representation. However, the GCN aggregating mechanism fails to generalize to networks with hete…