4 papers · 1 filter
NodeJEPA: Structure-Conditioned Latent Prediction for Node-Level Graph Self-Supervised Learning
Tinghe Zhang, Jian Xu, Jiaheng Chen +3
Self-supervised learning on graphs is largely shaped by contrastive methods that depend on carefully designed augmentations, and by generative methods that reconstruct node attribu…
BLEG: LLM Functions as Powerful fMRI Graph-Enhancer for Brain Network Analysis
Rui Dong, Zitong Wang, Jiaxing Li +2
Graph Neural Networks (GNNs) have been widely used in diverse brain network analysis tasks based on preprocessed functional magnetic resonance imaging (fMRI) data. However, their p…
Instance-Prototype Affinity Learning for Non-Exemplar Continual Graph Learning
Lei Song, Jiaxing Li, Shihan Guan +1
Graph Neural Networks (GNN) endure catastrophic forgetting, undermining their capacity to preserve previously acquired knowledge amid the assimilation of novel information. Rehears…
Topology-Aware Dynamic Reweighting for Distribution Shifts on Graph
Weihuang Zheng, Jiashuo Liu, Jiaxing Li +3
Graph Neural Networks (GNNs) are widely used for node classification tasks but often fail to generalize when training and test nodes come from different distributions, limiting the…