Accelerating SNN Training with Stochastic Parallelizable Spiking Neurons
Author:
Affiliation:
1. Université de Sherbrooke,Department of Electrical and Computer Engineering,Sherbrooke,QC,Canada
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10190990/10190992/10191884.pdf?arnumber=10191884
Reference42 articles.
1. Legendre memory units: Continuous-time representation in recurrent neural networks;voelker;Advances in neural information processing systems,2019
2. Surrogate Gradient Learning in Spiking Neural Networks: Bringing the Power of Gradient-Based Optimization to Spiking Neural Networks
3. Accelerating recurrent neural network training using sequence bucketing and multi-GPU data parallelization
4. A Review of the Integrate-and-fire Neuron Model: I. Homogeneous Synaptic Input
Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Direct training high-performance deep spiking neural networks: a review of theories and methods;Frontiers in Neuroscience;2024-07-31
2. Parallel Spiking Unit for Efficient Training of Spiking Neural Networks;2024 International Joint Conference on Neural Networks (IJCNN);2024-06-30
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