SOR-SNN employs Self-Organizing Regulation networks to reorganize a single SNN into sparse pathways, achieving better performance, energy efficiency, memory use, backward transfer, and self-repair on continual learning tasks including CIFAR100 and ImageNet.
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Adaptive Reorganization of Neural Pathways for Continual Learning with Spiking Neural Networks
SOR-SNN employs Self-Organizing Regulation networks to reorganize a single SNN into sparse pathways, achieving better performance, energy efficiency, memory use, backward transfer, and self-repair on continual learning tasks including CIFAR100 and ImageNet.