Dec 10, 2021 · To address this problem, in this article, we propose a family of aligned vertex convolutional network (AVCN) models that focus on learning ...

Feb 26, 2019 · In this paper, we develop a new aligned vertex convolutional network model to learn multi-scale local-level vertex features for graph classification.

To address this problem, in this article, we propose a family of aligned vertex convolutional network (AVCN) models that focus on learning multiscale fea- tures ...

Abstract. In this paper, we develop a novel Aligned-Spatial Graph Con- volutional Network (ASGCN) model to learn effective features for graph classification ...

This paper develops a new aligned vertex convolutional network model to learn multi-scale local-level vertex features for graph classification, ...

Dec 16, 2021 · Cui, Lixin, Bai, Lu, Xiao, Bai et al. (2 more authors) (2021) Learning Aligned Vertex Convolutional Networks for Graph Classification.

Feb 26, 2019 · In this paper, we develop a new aligned vertex convolutional network model to learn multi-scale local-level vertex features for graph ...

Oct 22, 2024 · To address this problem, in this article, we propose a family of aligned vertex convolutional network (AVCN) models that focus on learning ...

In this paper, we develop a novel Aligned-Spatial Graph Convolutional Network (ASGCN) model to learn effective features for graph classification.

Abstract—This paper proposes a novel Quantum Spatial. Graph Convolutional Neural Network (QSGCNN) model that can directly learn a classification function ...