14 citations · 20 across the 6 of their papers we have counts for
6 papers
Contrastive Disentangled Learning on Graph for Node Classification
Xiaojuan Zhang, Jun Fu, Shuang Li
Contrastive learning methods have attracted considerable attention due to their remarkable success in analyzing graph-structured data. Inspired by the success of contrastive learni…
Variational Disentangled Graph Auto-Encoders for Link Prediction
Jun Fu, Xiaojuan Zhang, Shuang Li +1
With the explosion of graph-structured data, link prediction has emerged as an increasingly important task. Embedding methods for link prediction utilize neural networks to generat…
Fine-Grained Control of Artistic Styles in Image Generation
Xin Miao, Huayan Wang, Jun Fu +3
Recent advances in generative models and adversarial training have enabled artificially generating artworks in various artistic styles. It is highly desirable to gain more control…
Bayesian Spatio-Temporal Graph Convolutional Network for Traffic Forecasting
Jun Fu, Wei Zhou, Zhibo Chen
In traffic forecasting, graph convolutional networks (GCNs), which model traffic flows as spatio-temporal graphs, have achieved remarkable performance. However, existing GCN-based…
Sequential Reinforced 360-Degree Video Adaptive Streaming with Cross-user Attentive Network
Jun Fu, Zhibo Chen, Xiaoming Chen +1
In the tile-based 360-degree video streaming, predicting user's future viewpoints and developing adaptive bitrate (ABR) algorithms are essential for optimizing user's quality of ex…
Residual Squeeze-and-Excitation Network for Fast Image Deraining
Jun Fu, Jianfeng Xu, Kazuyuki Tasaka +1
Image deraining is an important image processing task as rain streaks not only severely degrade the visual quality of images but also significantly affect the performance of high-l…