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20192026
most citedTraining Spiking Neural Networks with Local Tandem Learning

20 citations · 131 across the 43 of their papers we have counts for

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Showing 2019Show all

5 papers · 1 filter

cs.NE2019★ 7 cited

Deep Spiking Neural Networks for Large Vocabulary Automatic Speech Recognition

Jibin Wu, Emre Yilmaz, Malu Zhang +2

Artificial neural networks (ANN) have become the mainstream acoustic modeling technique for large vocabulary automatic speech recognition (ASR). A conventional ANN features a multi…

cs.NE2019★ 7 cited

Neural Population Coding for Effective Temporal Classification

Zihan Pan, Jibin Wu, Yansong Chua +2

Neural encoding plays an important role in faithfully describing the temporally rich patterns, whose instances include human speech and environmental sounds. For tasks that involve…

cs.SD2019

An efficient and perceptually motivated auditory neural encoding and decoding algorithm for spiking neural networks

Zihan Pan, Yansong Chua, Jibin Wu +3

Auditory front-end is an integral part of a spiking neural network (SNN) when performing auditory cognitive tasks. It encodes the temporal dynamic stimulus, such as speech and audi…

cs.NE2019

A Tandem Learning Rule for Effective Training and Rapid Inference of Deep Spiking Neural Networks

Jibin Wu, Yansong Chua, Malu Zhang +3

Spiking neural networks (SNNs) represent the most prominent biologically inspired computing model for neuromorphic computing (NC) architectures. However, due to the non-differentia…

cs.NE2019★ 11 cited

Deep Spiking Neural Network with Spike Count based Learning Rule

Jibin Wu, Yansong Chua, Malu Zhang +3

Deep spiking neural networks (SNNs) support asynchronous event-driven computation, massive parallelism and demonstrate great potential to improve the energy efficiency of its synch…