38 citations · 40 across the 4 of their papers we have counts for
4 papers
Gradient Scaling on Deep Spiking Neural Networks with Spike-Dependent Local Information
Seongsik Park, Jeonghee Jo, Jongkil Park +9
Deep spiking neural networks (SNNs) are promising neural networks for their model capacity from deep neural network architecture and energy efficiency from SNNs' operations. To tra…
Highly-scalable stochastic neuron based on Ovonic Threshold Switch (OTS) and its applications in Restricted Boltzmann Machine (RBM)
Seong-il Im, Hyejin Lee, Jaesang Lee +6
Interest in Restricted Boltzmann Machine (RBM) is growing as a generative stochastic artificial neural network to implement a novel energy-efficient machine-learning (ML) technique…
Frequency-tunable nano-oscillator based on Ovonic Threshold Switch (OTS)
Seon Jeong Kim, Seong Won Cho, Hyejin Lee +11
Nano-oscillator devices are gaining more and more attention as a prerequisite for developing novel energy-efficient computing systems based on coupled oscillators. Here, we introdu…
A highly scalable and energy-efficient artificial neuron using an Ovonic Threshold Switch (OTS) featuring the spike-frequency adaptation and chaotic activity
Milim Lee, Youngjo Kim, Seong Won Cho +5
As an essential building block for developing a large-scale brain-inspired computing system, we present a highly scalable and energy-efficient artificial neuron device composed of…