T2FSNN: Deep Spiking Neural Networks with Time-to-first-spike Coding

E. D. Adrian, “The impulses produced by sensory nerve endings,” The Journal of Physiology , vol. 61, no. 1, pp. 49–72, 1926

1926

Earlier work this paper cites.

W. Maass, “Networks of spiking neurons: the third generation of neural network models,” Neural Networks , vol. 10, no. 9, pp. 1659–1671, 1997

1997

Earlier work this paper cites.

S. Thorpe et al. , “Spike-based strategies for rapid processing,” Neural Networks , vol. 14, no. 6-7, pp. 715–725, 2001

2001

Earlier work this paper cites.

D. A. Butts et al. , “Temporal precision in the neural code and the timescales of natural vision,” Nature , vol. 449, no. 7158, p. 92, 2007

2007

Earlier work this paper cites.

M. A. Montemurro et al. , “Phase-of-firing coding of natural visual stimuli in primary visual cortex,” Current Biology , vol. 18, no. 5, pp. 375–380, 2008

2008

Earlier work this paper cites.

P. Merolla et al. , “A million spiking-neuron integrated circuit with a scalable communication network and interface,” Science , vol. 345, no. 6197, pp. 668–673, 2014

2014

Earlier work this paper cites.

S. B. Furber et al. , “The spinnaker project,” Proceedings of the IEEE , vol. 102, no. 5, pp. 652–665, 2014

2014

Earlier work this paper cites.

S. Han et al. , “Learning both weights and connections for efficient neural network,” in NIPS , 2015

2015

Cited alongside, same era.

P. U. Diehl et al. , “Fast-classifying, high-accuracy spiking deep networks through weight and threshold balancing,” in IJCNN , 2015

2015

Cited alongside, same era.

B. Rueckauer et al. , “Conversion of continuous-valued deep networks to efficient event-driven networks for image classification,” Frontiers in Neuroscience , vol. 11, p. 682, 2017

2017

Cited alongside, same era.

S. Park et al. , “Quantized memory-augmented neural networks,” in AAAI , 2018

2018

Cited alongside, same era.

Y. Jin et al. , “Hybrid macro/micro level backpropagation for training deep spiking neural networks,” in NIPS , 2018

2018

Cited alongside, same era.

B. Rueckauer and S. Liu, “Conversion of analog to spiking neural networks using sparse temporal coding,” in ISCAS , 2018

2018

Later among the works it cites.

M. Tan and Q. V. Le, “Efficientnet: Rethinking model scaling for convolutional neural networks,” in ICML , 2019

2019

Later among the works it cites.

Y. Wu et al. , “Direct training for spiking neural networks: Faster, larger, better,” in AAAI , 2019

2019

Later among the works it cites.

S. Park et al. , “Fast and efficient information transmission with burst spikes in deep spiking neural networks,” in DAC , 2019

2019

Later among the works it cites.

L. Zhang et al. , “Tdsnn: From deep neural networks to deep spike neural networks with temporal-coding,” in AAAI , 2019

2019

Later among the works it cites.