1 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.LG2026
Time-varying Interaction Graph ODE for Dynamic Graph Representation Learning
Xiaoyi Wang, Zhiqiang Wang, Jianqing Liang +4
Graph neural Ordinary Differential Equations (ODE) combine neural ODE with the message passing mechanism of Graph Neural Networks (GNN), providing a continuous-time modeling method…
cs.LG2021★ 1 cited
Optimizing Memory Efficiency of Graph Neural Networks on Edge Computing Platforms
Ao Zhou, Jianlei Yang, Yeqi Gao +7
Graph neural networks (GNN) have achieved state-of-the-art performance on various industrial tasks. However, the poor efficiency of GNN inference and frequent Out-Of-Memory (OOM) p…
cs.LG2020★ 1 cited
DP-Net: Dynamic Programming Guided Deep Neural Network Compression
Dingcheng Yang, Wenjian Yu, Ao Zhou +3
In this work, we propose an effective scheme (called DP-Net) for compressing the deep neural networks (DNNs). It includes a novel dynamic programming (DP) based algorithm to obtain…