49 citations · 67 across the 4 of their papers we have counts for
9 papers
Optimized Potential Initialization for Low-latency Spiking Neural Networks
Tong Bu, Jianhao Ding, Zhaofei Yu +1
Spiking Neural Networks (SNNs) have been attached great importance due to the distinctive properties of low power consumption, biological plausibility, and adversarial robustness.…
Pruning of Deep Spiking Neural Networks through Gradient Rewiring
Yanqi Chen, Zhaofei Yu, Wei Fang +2
Spiking Neural Networks (SNNs) have been attached great importance due to their biological plausibility and high energy-efficiency on neuromorphic chips. As these chips are usually…
Optimal ANN-SNN Conversion for Fast and Accurate Inference in Deep Spiking Neural Networks
Jianhao Ding, Zhaofei Yu, Yonghong Tian +1
Spiking Neural Networks (SNNs), as bio-inspired energy-efficient neural networks, have attracted great attentions from researchers and industry. The most efficient way to train dee…
Towards the Next Generation of Retinal Neuroprosthesis: Visual Computation with Spikes
Zhaofei Yu, Jian K. Liu, Shanshan Jia +4
Neuroprosthesis, as one type of precision medicine device, is aiming for manipulating neuronal signals of the brain in a closed-loop fashion, together with receiving stimulus from…
Reconstruction of Natural Visual Scenes from Neural Spikes with Deep Neural Networks
Yichen Zhang, Shanshan Jia, Yajing Zheng +5
Neural coding is one of the central questions in systems neuroscience for understanding how the brain processes stimulus from the environment, moreover, it is also a cornerstone fo…
Probabilistic Inference of Binary Markov Random Fields in Spiking Neural Networks through Mean-field Approximation
Yajing Zheng, Shanshan Jia, Zhaofei Yu +3
Recent studies have suggested that the cognitive process of the human brain is realized as probabilistic inference and can be further modeled by probabilistic graphical models like…