Xing Wang
16 Papers
Xing Wang is an academic researcher. The author has contributed to research in topics: Computer science & Timestamp. The author has an hindex of 1, co-authored 6 publications.
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Papers
Large-scale Urban Cellular Traffic Generation via Knowledge-Enhanced GANs with Multi-Periodic Patterns
Shuodi Hui,Huandong Wang,Tong Liu,Xinghao Yang,Xing Wang,Jun Feng,Lin Zhu,Chao Deng,Pan Hui,Depeng Jin,Yong Li +10 more
- 04 Aug 2023
TL;DR: A knowledge-enhanced GAN with multi-periodic patterns to generate large-scale cellular traffic based on the urban environment that outperforms three state-of-art generation models and achieves good generalization and robustness in generating traffic for urban cellular networks without training data in the surrounding areas.
12
Empowering Spatial Knowledge Graph for Mobile Traffic Prediction
Jiahui Gong,Yu Liu,Tong Li,Haoye Chai,Xing Wang,Jun Feng,Chao Deng,Depeng Jin,Yong Li +8 more
- 13 Nov 2023
TL;DR: A spatial knowledge graph is utilized to represent spatial information and add important urban components to augment it making it a more effective tool for capturing environmental information and significantly outperforms the state-of-the-art models by over 10% in mobile traffic prediction.
9
Network Traffic Overload Prediction with Temporal Graph Attention Convolutional Networks
Qiaohong Yu,Huandong Wang,Tong Li,Depeng Jin,Xing Wang,Lin Zhu,Jun-Huan Feng,Chao Deng +7 more
- 16 May 2022
TL;DR: This paper adopts the soft-attention mechanism to fuse the threshold-based discrete and continuous time series characteristics to predict traffic overload and outperforms the state-of-the-art algorithms by 4.07%.
8
Adaptive Hybrid Spatial-Temporal Graph Neural Network for Cellular Traffic Prediction
Xing Wang,Kexin Yang,Zhendong Wang,Junlan Feng,Lin Zhu,Juan Zhao,Chao Deng +6 more
TL;DR: Huang et al. as discussed by the authors proposed a novel deep learning network architecture, Adaptive Hybrid Spatial-Temporal Graph Neural Network (AHSTGNN), to tackle the cellular traffic prediction problem.
FaceChain: A Playground for Identity-Preserving Portrait Generation
Yang Liu,Cheng Yu,Lei Shang,Ziheng Wu,Xing Wang,Yuze Zhao,Ling-Xing Zhu,Chen Cheng,Weitao Chen,Chao Xu,Haoyu Xie,Yuan Yao,Wenmeng Zhou,Ying-Jie Chen,Xuansong Xie,Baigui Sun +15 more
TL;DR: FaceChain is a personalized portrait generation framework that combines a series of customized image-generation model and a rich set of face-related perceptual understanding models to tackle aforementioned challenges and to generate truthful personalized portraits, with only a handful of portrait images as input.