23 citations · 92 across the 14 of their papers we have counts for
6 papers · 1 filter
Spatial-Temporal Tensor Graph Convolutional Network for Traffic Prediction
Xuran Xu, Tong Zhang, Chunyan Xu +2
Accurate traffic prediction is crucial to the guidance and management of urban traffics. However, most of the existing traffic prediction models do not consider the computational b…
Graph Wasserstein Correlation Analysis for Movie Retrieval
Xueya Zhang, Tong Zhang, Xiaobin Hong +2
Movie graphs play an important role to bridge heterogenous modalities of videos and texts in human-centric retrieval. In this work, we propose Graph Wasserstein Correlation Analysi…
Graph Inference Learning for Semi-supervised Classification
Chunyan Xu, Zhen Cui, Xiaobin Hong +3
In this work, we address semi-supervised classification of graph data, where the categories of those unlabeled nodes are inferred from labeled nodes as well as graph structures. Re…
Dual-Attention Graph Convolutional Network
Xueya Zhang, Tong Zhang, Wenting Zhao +2
Graph convolutional networks (GCNs) have shown the powerful ability in text structure representation and effectively facilitate the task of text classification. However, challenges…
Gaussian-Induced Convolution for Graphs
Jiatao Jiang, Zhen Cui, Chunyan Xu +1
Learning representation on graph plays a crucial role in numerous tasks of pattern recognition. Different from grid-shaped images/videos, on which local convolution kernels can be…
When Work Matters: Transforming Classical Network Structures to Graph CNN
Wenting Zhao, Chunyan Xu, Zhen Cui +4
Numerous pattern recognition applications can be formed as learning from graph-structured data, including social network, protein-interaction network, the world wide web data, know…