Yuhang Li, Yufei Guo, Shanghang Zhang, Shikuang Deng, Yongqing Hai, Shi Gu. Differentiable Spike: Rethinking Gradient-Descent for Training Spiking Neural Networks. In Marc'Aurelio Ranzato, Alina Beygelzimer, Yann N. Dauphin, Percy Liang, Jennifer Wortman Vaughan, editors, Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual. pages 23426-23439, 2021. [doi]
@inproceedings{LiGZDHG21,
title = {Differentiable Spike: Rethinking Gradient-Descent for Training Spiking Neural Networks},
author = {Yuhang Li and Yufei Guo and Shanghang Zhang and Shikuang Deng and Yongqing Hai and Shi Gu},
year = {2021},
url = {https://proceedings.neurips.cc/paper/2021/hash/c4ca4238a0b923820dcc509a6f75849b-Abstract.html},
researchr = {https://researchr.org/publication/LiGZDHG21},
cites = {0},
citedby = {0},
pages = {23426-23439},
booktitle = {Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual},
editor = {Marc'Aurelio Ranzato and Alina Beygelzimer and Yann N. Dauphin and Percy Liang and Jennifer Wortman Vaughan},
}