HGNN combines fixed-connection CGNN and adaptive-connection IGNN branches with a graph pooling-unpooling module to achieve state-of-the-art EEG-based depression detection on two public datasets.
IEEE Transactions on Affective Computing 11(3), 532–541 (2018)
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A Hybrid Graph Neural Network for Enhanced EEG-Based Depression Detection
HGNN combines fixed-connection CGNN and adaptive-connection IGNN branches with a graph pooling-unpooling module to achieve state-of-the-art EEG-based depression detection on two public datasets.