11 citations · 13 across the 7 of their papers we have counts for
3 papers · 1 filter
Magic for the Age of Quantized DNNs
Yoshihide Sawada, Ryuji Saiin, Kazuma Suetake
Recently, the number of parameters in DNNs has explosively increased, as exemplified by LLMs (Large Language Models), making inference on small-scale computers more difficult. Mode…
Spiking Synaptic Penalty: Appropriate Penalty Term for Energy-Efficient Spiking Neural Networks
Kazuma Suetake, Takuya Ushimaru, Ryuji Saiin +1
Spiking neural networks (SNNs) are energy-efficient neural networks because of their spiking nature. However, as the spike firing rate of SNNs increases, the energy consumption doe…
SNN: Time Step Reduction of Spiking Surrogate Gradients for Training Energy Efficient Single-Step Spiking Neural Networks
Kazuma Suetake, Shin-ichi Ikegawa, Ryuji Saiin +1
As the scales of neural networks increase, techniques that enable them to run with low computational cost and energy efficiency are required. From such demands, various efficient n…