no code implementations • 28 May 2024 • Zebin You, Xinyu Zhang, Hanzhong Guo, Jingdong Wang, Chongxuan Li
The ultimate goal of generative models is to characterize the data distribution perfectly.
1 code implementation • 28 Mar 2024 • Sidi Yang, Binxiao Huang, Mingdeng Cao, Yatai Ji, Hanzhong Guo, Ngai Wong, Yujiu Yang
Existing enhancement models often optimize for high performance while falling short of reducing hardware inference time and power consumption, especially on edge devices with constrained computing and storage resources.
1 code implementation • 29 Jun 2023 • Jiahang Cao, Ziqing Wang, Hanzhong Guo, Hao Cheng, Qiang Zhang, Renjing Xu
In our paper, we put forward Spiking Denoising Diffusion Probabilistic Models (SDDPM), a new class of SNN-based generative models that achieve high sample quality.