Learning unbiased node representations for imbalanced samples in the gra...
Contrastive Learning (CL) has been proved to be a powerful self-supervis...
Most Graph Neural Networks follow the message-passing paradigm, assuming...
Social networks are considered to be heterogeneous graph neural networks...
Topology-imbalance is a graph-specific imbalance problem caused by the u...
Generative adversarial network (GAN) is widely used for generalized and
...
Graph Neural Networks (GNNs) have shown promising results on a broad spe...
Graph Neural Networks (GNNs) have been widely studied in various graph d...
Graph embedding is essential for graph mining tasks. With the prevalence...