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cs.NE2023
Spike Accumulation Forwarding for Effective Training of Spiking Neural Networks
Ryuji Saiin, Tomoya Shirakawa, Sota Yoshihara +2
In this article, we propose a new paradigm for training spiking neural networks (SNNs), spike accumulation forwarding (SAF). It is known that SNNs are energy-efficient but difficul…
cs.NE2022
Rethinking the role of normalization and residual blocks for spiking neural networks
Shin-ichi Ikegawa, Ryuji Saiin, Yoshihide Sawada +1
Biologically inspired spiking neural networks (SNNs) are widely used to realize ultralow-power energy consumption. However, deep SNNs are not easy to train due to the excessive fir…