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…
When Language Models Meet NeuroGraphs: Exploring Enhanced Agentic LLM Framework Towards Brain Network Analysis
Jiaxing Li, Rui Dong, Muyao Tang +1
Brain network analysis is crucial for understanding cognition and neurological disorders, yet existing deep learning methods mainly treat connectome analysis as a graph-to-logit cl…
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…
M3D-BFS: a Multi-stage Dynamic Fusion Strategy for Sample-Adaptive Multi-Modal Brain Network Analysis
Rui Dong, Xiaotong Zhang, Jiaxing Li +3
Multi-modal fusion is of great significance in neuroscience which integrates information from different modalities and can achieve better performance than uni-modal methods in down…