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20242026
most citedUMGAD: Unsupervised Multiplex Graph Anomaly Detection

3 citations · 6 across the 10 of their papers we have counts for

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6 papers · 1 filter

cs.NI2025★ 1 cited

A Survey on Open-Source Edge Computing Simulators and Emulators: The Computing and Networking Convergence Perspective

Jianpeng Qi, Chao Liu, Xiao Zhang +4

Edge computing, with its low latency, dynamic scalability, and location awareness, along with the convergence of computing and communication paradigms, has been successfully applie…

cs.NI2025

Efficient Information Updates in Compute-First Networking via Reinforcement Learning with Joint AoI and VoI

Jianpeng Qi, Chao Liu, Chengxiang Xu +3

Timely and efficient dissemination of service information is critical in compute-first networking systems, where user requests arrive dynamically and computing resources are constr…

cs.DB2025

Efficient Discovery of Motif Transition Process for Large-Scale Temporal Graphs

Zhiyuan Zheng, Jianpeng Qi, Jiantao Li +3

Understanding the dynamic transition of motifs in temporal graphs is essential for revealing how graph structures evolve over time, identifying critical patterns, and predicting fu…

cs.LG2025

ScaleGNN: Towards Scalable Graph Neural Networks via Adaptive High-order Neighboring Feature Fusion

Xiang Li, Jianpeng Qi, Haobing Liu +6

Graph Neural Networks (GNNs) have demonstrated impressive performance across diverse graph-based tasks by leveraging message passing to capture complex node relationships. However,…

cs.SI2025

Correlation-Attention Masked Temporal Transformer for User Identity Linkage Using Heterogeneous Mobility Data

Ziang Yan, Xingyu Zhao, Hanqing Ma +4

With the rise of social media and Location-Based Social Networks (LBSN), check-in data across platforms has become crucial for User Identity Linkage (UIL). These data not only reve…

cs.LG2025★ 2 cited

Spatiotemporal-aware Trend-Seasonality Decomposition Network for Traffic Flow Forecasting

Lingxiao Cao, Bin Wang, Guiyuan Jiang +2

Traffic prediction is critical for optimizing travel scheduling and enhancing public safety, yet the complex spatial and temporal dynamics within traffic data present significant c…