Efficient Spiking Neural Networks with Sparse Selective Activation for Continual Learning
Jiangrong Shen,
Wenyao Ni,
Qi Xu
et al.
Abstract:The next generation of machine intelligence requires the capability of continual learning to acquire new knowledge without forgetting the old one while conserving limited computing resources.
Spiking neural networks (SNNs), compared to artificial neural networks (ANNs), have more characteristics that align with biological neurons, which may be helpful as a potential gating function for knowledge maintenance in neural networks. Inspired by the selective sparse activation principle of context gating in biologic… Show more
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