90 citations · 136 across the 3 of their papers we have counts for
3 papers
cs.LG2019★ 90 cited
Learning Backtrackless Aligned-Spatial Graph Convolutional Networks for Graph Classification
Lu Bail, Lixin Cui, Yuhang Jiao +2
In this paper, we develop a novel Backtrackless Aligned-Spatial Graph Convolutional Network (BASGCN) model to learn effective features for graph classification. Our idea is to tran…
cs.LG2019★ 2 cited
Learning Vertex Convolutional Networks for Graph Classification
Lu Bai, Lixin Cui, Shu Wu +2
In this paper, we develop a new aligned vertex convolutional network model to learn multi-scale local-level vertex features for graph classification. Our idea is to transform the g…
cs.LG2018★ 44 cited
Graph Convolutional Neural Networks based on Quantum Vertex Saliency
Lu Bai, Yuhang Jiao, Luca Rossi +3
This paper proposes a new Quantum Spatial Graph Convolutional Neural Network (QSGCNN) model that can directly learn a classification function for graphs of arbitrary sizes. Unlike…