Neural Architecture Search for Spiking Neural Networks. (arXiv:2201.10355v1 [cs.NE])

Spiking Neural Networks (SNNs) have gained huge attention as a potential
energy-efficient alternative to conventional Artificial Neural Networks (ANNs)
due to their inherent high-sparsity activation. However, most prior SNN methods
use ANN-like architectures (e.g., VGG-Net or ResNet), which could provide
sub-optimal performance for temporal sequence processing of binary information
in SNNs. To address this, in this paper, we introduce a novel Neural
Architecture Search (NAS) approach for finding better SNN architectures.
Inspired by recent NAS approaches that find the optimal …

architecture arxiv networks neural architecture search neural networks search