42 citations · 117 across the 8 of their papers we have counts for
15 papers
Disentangled Spatiotemporal Graph Generative Models
Yuanqi Du, Xiaojie Guo, Hengning Cao +2
Spatiotemporal graph represents a crucial data structure where the nodes and edges are embedded in a geometric space and can evolve dynamically over time. Nowadays, spatiotemporal…
Black-box Node Injection Attack for Graph Neural Networks
Mingxuan Ju, Yujie Fan, Yanfang Ye +1
Graph Neural Networks (GNNs) have drawn significant attentions over the years and been broadly applied to vital fields that require high security standard such as product recommend…
Heterogeneous Temporal Graph Neural Network
Yujie Fan, Mingxuan Ju, Chuxu Zhang +2
Graph neural networks (GNNs) have been broadly studied on dynamic graphs for their representation learning, majority of which focus on graphs with homogeneous structures in the spa…
Knowledge-aware Coupled Graph Neural Network for Social Recommendation
Chao Huang, Huance Xu, Yong Xu +7
Social recommendation task aims to predict users' preferences over items with the incorporation of social connections among users, so as to alleviate the sparse issue of collaborat…
Detection of Illicit Drug Trafficking Events on Instagram: A Deep Multimodal Multilabel Learning Approach
Chuanbo Hu, Minglei Yin, Bin Liu +2
Social media such as Instagram and Twitter have become important platforms for marketing and selling illicit drugs. Detection of online illicit drug trafficking has become critical…
A Survey on Heterogeneous Graph Embedding: Methods, Techniques, Applications and Sources
Xiao Wang, Deyu Bo, Chuan Shi +3
Heterogeneous graphs (HGs) also known as heterogeneous information networks have become ubiquitous in real-world scenarios; therefore, HG embedding, which aims to learn representat…