Author

Xiangtao Li

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Preprint Aug 2026

A Network-driven Framework for Public Event Forecasting via Dynamic Interaction Network Evolution

Auto-ibDLM is proposed, a network-driven deep learning framework that represents events as dynamic interaction networks and predicts public event evolution through participant growth forecasting and consistently outperforms representative state-of-the-art methods in both forecasting accuracy and generalization capabili...

Jie Wei, Yue Liu, Xiaochuan Tang et al. · 0 citations

Aug 2026

Sadgae: doubly enhanced graph autoencoder with self-adaptive cell graph for single-cell RNA-Seq clustering

SaDGAE, an unsupervised deep graph autoencoder (GAE) framework that jointly models gene expression patterns and cell–cell relationships, achieves strong and competitive clustering performance, yielding biologically interpretable clusters and accurately recovering known marker gene patterns.

Xiang-Hui Liu, Yanmei Hu, Sheng-Lin Yang et al. · International Journal of Dat... · 0 citations