5 citations · 15 across the 11 of their papers we have counts for
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cs.CV2023
Adaptive Calibration: A Unified Conversion Framework of Spiking Neural Networks
Ziqing Wang, Yuetong Fang, Jiahang Cao +1
Spiking Neural Networks (SNNs) have emerged as a promising energy-efficient alternative to traditional Artificial Neural Networks (ANNs). Despite this, bridging the performance gap…
cs.NE2023★ 3 cited
AutoST: Training-free Neural Architecture Search for Spiking Transformers
Ziqing Wang, Qidong Zhao, Jinku Cui +2
Spiking Transformers have gained considerable attention because they achieve both the energy efficiency of Spiking Neural Networks (SNNs) and the high capacity of Transformers. How…
cs.NE2023★ 1 cited
Spiking Denoising Diffusion Probabilistic Models
Jiahang Cao, Ziqing Wang, Hanzhong Guo +3
Spiking neural networks (SNNs) have ultra-low energy consumption and high biological plausibility due to their binary and bio-driven nature compared with artificial neural networks…