Contrastive Brain Network Learning via Hierarchical Signed Graph Pooling Model
Contrastive Brain Network Learning via Hierarchical Signed Graph Pooling Model
Recently, brain networks have been widely adopted to study brain dynamics, brain development, and brain diseases. Graph representation learning techniques on brain functional networks can facilitate the discovery of novel biomarkers for clinical phenotypes and neurodegenerative diseases. However, current graph learning techniques have several issues on brain network mining. First, …