5 citations · 15 across the 11 of their papers we have counts for
6 papers · 1 filter
Spiking Diffusion Models
Jiahang Cao, Hanzhong Guo, Ziqing Wang +4
Recent years have witnessed Spiking Neural Networks (SNNs) gaining attention for their ultra-low energy consumption and high biological plausibility compared with traditional Artif…
Autonomous Driving with Spiking Neural Networks
Rui-Jie Zhu, Ziqing Wang, Leilani Gilpin +1
Autonomous driving demands an integrated approach that encompasses perception, prediction, and planning, all while operating under strict energy constraints to enhance scalability…
Spiking Wavelet Transformer
Yuetong Fang, Ziqing Wang, Lingfeng Zhang +3
Spiking neural networks (SNNs) offer an energy-efficient alternative to conventional deep learning by emulating the event-driven processing manner of the brain. Incorporating Trans…
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…
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…
Masked Spiking Transformer
Ziqing Wang, Yuetong Fang, Jiahang Cao +3
The combination of Spiking Neural Networks (SNNs) and Transformers has attracted significant attention due to their potential for high energy efficiency and high-performance nature…