Aili Wang

most citedSDiT: Spiking Diffusion Model with Transformer

1 citations · 1 across the 2 of their papers we have counts for

collaborators

2 papers

cs.CV2024★ 1 cited

SDiT: Spiking Diffusion Model with Transformer

Shu Yang, Hanzhi Ma, Chengting Yu +2

Spiking neural networks (SNNs) have low power consumption and bio-interpretable characteristics, and are considered to have tremendous potential for energy-efficient computing. How…

physics.app-ph2023

Sub-5-nm Ultra-thin In $_{2}$ O $_{3}$ Transistors for High-Performance and Low-Power Electronic Applications

Linqiang Xu, Lianqiang Xu, Jun Lan +7

Ultra-thin (UT) oxide semiconductors are promising candidates for back-end-of-line (BEOL) compatible transistors and monolithic three-dimensional integration. Experimentally, UT in…

SDiT: Spiking Diffusion Model with Transformer

Sub-5-nm Ultra-thin In2​O3​ Transistors for High-Performance and Low-Power Electronic Applications

Sub-5-nm Ultra-thin In $_{2}$ O $_{3}$ Transistors for High-Performance and Low-Power Electronic Applications