SA-HGNN combines sample-adaptive graph construction, hyperbolic graph convolution, and attention pooling to model hierarchical brain networks from EEG for improved depression recognition.
Over a billion people living with mental health conditions – services require urgent scale-up,
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SA-HGNN: Sample-Adaptive Hyperbolic Graph Neural Network for EEG-Based Depression Recognition
SA-HGNN combines sample-adaptive graph construction, hyperbolic graph convolution, and attention pooling to model hierarchical brain networks from EEG for improved depression recognition.