1 citations · 2 across the 2 of their papers we have counts for
3 papers
cs.AR2021★ 1 cited
Effects of VLSI Circuit Constraints on Temporal-Coding Multilayer Spiking Neural Networks
Yusuke Sakemi, Takashi Morie, Takeo Hosomi +1
The spiking neural network (SNN) has been attracting considerable attention not only as a mathematical model for the brain, but also as an energy-efficient information processing m…
cs.LG2020
Model-Size Reduction for Reservoir Computing by Concatenating Internal States Through Time
Yusuke Sakemi, Kai Morino, Timothée Leleu +1
Reservoir computing (RC) is a machine learning algorithm that can learn complex time series from data very rapidly based on the use of high-dimensional dynamical systems, such as r…
cs.NE2020★ 1 cited
A Supervised Learning Algorithm for Multilayer Spiking Neural Networks Based on Temporal Coding Toward Energy-Efficient VLSI Processor Design
Yusuke Sakemi, Kai Morino, Takashi Morie +1
Spiking neural networks (SNNs) are brain-inspired mathematical models with the ability to process information in the form of spikes. SNNs are expected to provide not only new machi…