16 citations · 33 across the 3 of their papers we have counts for
3 papers
cs.NE2018★ 10 cited
Deep Learning with the Random Neural Network and its Applications
Yonghua Yin
The random neural network (RNN) is a mathematical model for an "integrate and fire" spiking network that closely resembles the stochastic behaviour of neurons in mammalian brains.…
cs.LG2016★ 7 cited
Nonnegative autoencoder with simplified random neural network
Yonghua Yin, Erol Gelenbe
This paper proposes new nonnegative (shallow and multi-layer) autoencoders by combining the spiking Random Neural Network (RNN) model, the network architecture typical used in deep…
cs.NE2016★ 16 cited
Deep Learning in Multi-Layer Architectures of Dense Nuclei
Yonghua Yin, Erol Gelenbe
We assume that, within the dense clusters of neurons that can be found in nuclei, cells may interconnect via soma-to-soma interactions, in addition to conventional synaptic connect…