Adaptive Reorganization of Neural Pathways for Continual Learning with Spiking Neural Networks

ArXi:2309.09550v4 Announce Type: replace-cross The human brain can self-organize rich and diverse sparse neural pathways to incrementally master hundreds of cognitive tasks. However, most existing continual learning algorithms for deep artificial and spiking neural networks are unable to adequately auto-regulate the limited resources in the network, which leads to performance drop along with energy consumption rise as the increase of tasks.