1 code implementation • 23 Oct 2023 • Qiugang Zhan, Xiurui Xie, Guisong Liu, Malu Zhang
In this paper, we propose an efficient spiking variational autoencoder (ESVAE) that constructs an interpretable latent space distribution and design a reparameterizable spiking sampling method.
1 code implementation • 13 Dec 2021 • Guisong Liu, Wenjie Deng, Xiurui Xie, Li Huang, Huajin Tang
Specifically, we propose a directly-trained deep spiking reinforcement learning architecture based on the Leaky Integrate-and-Fire (LIF) neurons and Deep Q-Network (DQN).
1 code implementation • 23 Sep 2018 • Jean-Paul Ainam, Ke Qin, Guisong Liu
We apply a max filter operation to non-overlapping sub-regions on the high feature representation before element-wise multiplied with the output of the second branch.
1 code implementation • 13 Sep 2018 • Jean-Paul Ainam, Ke Qin, Guisong Liu, Guangchun Luo
Finally, we assign a non-uniform label distribution to the generated samples and define a regularized loss function for training.