1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.LG2024
GrassNet: State Space Model Meets Graph Neural Network
Gongpei Zhao, Tao Wang, Yi Jin +3
Designing spectral convolutional networks is a formidable task in graph learning. In traditional spectral graph neural networks (GNNs), polynomial-based methods are commonly used t…
cs.AR2023★ 1 cited
NPS: A Framework for Accurate Program Sampling Using Graph Neural Network
Yuanwei Fang, Zihao Liu, Yanheng Lu +7
With the end of Moore's Law, there is a growing demand for rapid architectural innovations in modern processors, such as RISC-V custom extensions, to continue performance scaling.…