no code implementations • 26 Feb 2024 • Man Wu, Xin Zheng, Qin Zhang, Xiao Shen, Xiong Luo, Xingquan Zhu, Shirui Pan
Graph learning plays a pivotal role and has gained significant attention in various application scenarios, from social network analysis to recommendation systems, for its effectiveness in modeling complex data relations represented by graph structural data.
1 code implementation • 5 Jan 2024 • Yunpeng Yao, Man Wu, Zheng Chen, Renyuan Zhang
This paper proposes a general training framework that enhances feature learning and activation efficiency within a limited time step, providing a new solution for more energy-efficient SNNs.
no code implementations • 8 Mar 2021 • Man Wu, Shirui Pan, Lan Du, Xingquan Zhu
By generating multiple graphs at different distance levels, based on the adjacency matrix, we develop a long-short distance attention model to model these graphs.