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Found 2 papers, 1 papers with code
Accelerating SNN Training with Stochastic Parallelizable Spiking Neurons
In this paper, we propose the Stochastic Parallelizable Spiking Neuron (SPSN) to overcome the sequential training limitation of LIF neurons.
Efficient spike encoding algorithms for neuromorphic speech recognition
Finally, we show that several encoding methods result in improved performance over the conventional deep learning baseline in certain cases, further demonstrating the power of spike encoding algorithms in the encoding of real-valued signals and that neuromorphic implementation has the potential to outperform state of the art techniques.
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