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In recent years, spiking neural networks (SNNs) have received extensive attention in brain-inspired intelligence due to their rich spatially-temporal dynamics, various encoding methods, and event-driven characteristics that naturally fit the neuromorphic hardware.
The impulses produced by sensory nerve-endings: Part II. The response of a Single End-Organ
Edgar D Adrian and Yngve Zotterman · 1926
Earlier work this paper cites.
A quantitative description of membrane current and its application to conduction and excitation in nerve
Alan L Hodgkin and Andrew F Huxley · 1952
Earlier work this paper cites.
The perceptron: a probabilistic model for information storage and organization in the brain
Frank Rosenblatt · 1958
Earlier work this paper cites.
Neuronal population coding of movement direction
Apostolos P Georgopoulos, Andrew B Schwartz, et al · 1986
Earlier work this paper cites.
Learning representations by back-propagating errors
David E Rumelhart, Geoffrey E Hinton, et al · 1986
Earlier work this paper cites.
Networks of spiking neurons: the third generation of neural network models
Wolfgang Maass · 1997
Earlier work this paper cites.
Synaptic modifications in cultured hippocampal neurons: dependence on spike timing, synaptic strength, and postsynaptic cell type
Guo-qiang Bi and Mu-ming Poo · 1998
Earlier work this paper cites.
The MNIST database of handwritten digits
Yann LeCun · 1998
Earlier work this paper cites.
Rank order coding
Simon Thorpe and Jacques Gautrais · 1998
Earlier work this paper cites.
Theoretical neuroscience: computational and mathematical modeling of neural systems
Peter Dayan, Laurence F Abbott, et al · 2003
Earlier work this paper cites.
Spike-timing dynamics of neuronal groups
Eugene M Izhikevich, Joseph A Gally, et al · 2004
Earlier work this paper cites.
Motifs in brain networks
Olaf Sporns, Rolf Kötter, et al · 2004
Earlier work this paper cites.
Spike times make sense
Rufin VanRullen, Rudy Guyonneau, et al · 2005
Earlier work this paper cites.
A fast learning algorithm for deep belief nets
Geoffrey E Hinton, Simon Osindero, et al · 2006
Earlier work this paper cites.
Parallel network simulations with NEURON
Michele Migliore, C Cannia, et al · 2006
Earlier work this paper cites.
Nest (neural simulation tool)
Marc-Oliver Gewaltig and Markus Diesmann · 2007
Earlier work this paper cites.
Learning multiple layers of features from tiny images
Alex Krizhevsky, Geoffrey Hinton, et al · 2009
Earlier work this paper cites.
How auto-encoders could provide credit assignment in deep networks via target propagation
Yoshua Bengio · 2014
Earlier work this paper cites.
Neurogrid: A mixed-analog-digital multichip system for large-scale neural simulations
Ben Varkey Benjamin, Peiran Gao, et al · 2014
Earlier work this paper cites.
The spinnaker project
Steve B Furber, Francesco Galluppi, et al · 2014
Earlier work this paper cites.
Truenorth: Design and tool flow of a 65 mw 1 million neuron programmable neurosynaptic chip
Filipp Akopyan, Jun Sawada, et al · 2015
Earlier work this paper cites.
Spiking deep convolutional neural networks for energy-efficient object recognition
Yongqiang Cao, Yang Chen, et al · 2015
Earlier work this paper cites.
Unsupervised learning of digit recognition using spike-timing-dependent plasticity
Peter U Diehl and Matthew Cook · 2015
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Converting static image datasets to spiking neuromorphic datasets using saccades
Garrick Orchard, Ajinkya Jayawant, et al · 2015
Cited alongside, same era.
Diverse synaptic plasticity mechanisms orchestrated to form and retrieve memories in spiking neural networks
Friedemann Zenke, Everton J Agnes, et al · 2015
Cited alongside, same era.
Random synaptic feedback weights support error backpropagation for deep learning
Timothy P Lillicrap, Daniel Cownden, et al · 2016
Cited alongside, same era.
Xnor-net: Imagenet classification using binary convolutional neural networks
Mohammad Rastegari, Vicente Ordonez, et al · 2016
Cited alongside, same era.
A dendritic disinhibitory circuit mechanism for pathway-specific gating
Going deeper in spiking neural networks: VGG and residual architectures
Abhronil Sengupta, Yuting Ye, et al · 2019
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Brian 2, an intuitive and efficient neural simulator
Marcel Stimberg, Romain Brette, et al · 2019
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LISNN: Improving Spiking Neural Networks with Lateral Interactions for Robust Object Recognition
Xiang Cheng, Yunzhe Hao, et al · 2020
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Optimal Conversion of Conventional Artificial Neural Networks to Spiking Neural Networks
Shikuang Deng and Shi Gu · 2020
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Rethinking the performance comparison between SNNS and ANNS
Lei Deng, Yujie Wu, et al · 2020
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A biologically plausible supervised learning method for spiking neural networks using the symmetric STDP rule
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Guangyu Robert Yang, John D Murray, et al · 2016
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A low power, fully event-based gesture recognition system
Arnon Amir, Brian Taba, et al · 2017
Cited alongside, same era.
PIX2NVS: Parameterized conversion of pixel-domain video frames to neuromorphic vision streams
Yin Bi and Yiannis Andreopoulos · 2017
Cited alongside, same era.
Cifar10-dvs: an event-stream dataset for object classification
Hongmin Li, Hanchao Liu, et al · 2017
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Conversion of continuous-valued deep networks to efficient event-driven networks for image classification
Bodo Rueckauer, Iulia-Alexandra Lungu, et al · 2017
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Distilled Binary Neural Network for Monaural Speech Separation
Xiuyi Chen, Guangcan Liu, et al · 2018
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Loihi: A neuromorphic manycore processor with on-chip learning
Mike Davies, Narayan Srinivasa, et al · 2018
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Yunzhe Hao, Xuhui Huang, et al · 2020
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Pruning of Deep Spiking Neural Networks through Gradient Rewiring
Yanqi Chen, Zhaofei Yu, et al · 2021
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Deep residual learning in spiking neural networks
Wei Fang, Zhaofei Yu, et al · 2021
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Learning without feedback: Fixed random learning signals allow for feedforward training of deep neural networks
Charlotte Frenkel, Martin Lefebvre, et al · 2021
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Advancing Deep Residual Learning by Solving the Crux of Degradation in Spiking Neural Networks
Yifan Hu, Yujie Wu, et al · 2021
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Exploiting Spiking Dynamics with Spatial-temporal Feature Normalization in Graph Learning
Mingkun Xu, Yujie Wu, et al · 2021
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Population-coding and Dynamic-neurons improved Spiking Actor Network for Reinforcement Learning
Duzhen Zhang, Tielin Zhang, et al · 2021
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Self-backpropagation of synaptic modifications elevates the efficiency of spiking and artificial neural networks
Tielin Zhang, Xiang Cheng, et al · 2021
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Tuning convolutional spiking neural network with biologically plausible reward propagation
Tielin Zhang, Shuncheng Jia, et al · 2021
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Neuron type classification in rat brain based on integrative convolutional and tree-based recurrent neural networks
Tielin Zhang, Yi Zeng, et al · 2021
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Going Deeper With Directly-Trained Larger Spiking Neural Networks
Hanle Zheng, Yujie Wu, et al · 2021
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SpikingJelly
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Spiking Graph Convolutional Networks
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