Structure-Adaptive Threshold Learning via sparse representation for Spiking Graph Neural Network
Experimental results validate the effectiveness of the structure-adaptive threshold mechanism for low-power spiking graph learning and design an alternating soft-fusion-hard-grouping training strategy that decouples structure-aware threshold generation from pattern-specific threshold optimization.