Land Deformation Prediction via Slope-Aware Graph Neural Networks. - Fan Zhou 002; Rongfan Li; Goce Trajcevski; Kunpeng Zhang 001 (AAAI, 2021)

A hybrid code representation learning approach for predicting method names. - Fengyi Zhang; Bihuan Chen 001; Rongfan Li; Xin Peng 001 (J. Syst. Softw., 2021)

Dynamic Manifold Learning for Land Deformation Forecasting. - Fan Zhou 002; Rongfan Li; Qiang Gao 003; Goce Trajcevski; Kunpeng Zhang 001; Ting Zhong (AAAI, 2022)

A Probabilistic Framework for Land Deformation Prediction (Student Abstract). - Rongfan Li; Fan Zhou 002; Goce Trajcevski; Kunpeng Zhang 001; Ting Zhong (AAAI, 2022)

Probabilistic Fine-Grained Urban Flow Inference with Normalizing Flows. - Ting Zhong; Haoyang Yu 003; Rongfan Li; Xovee Xu; Xucheng Luo; Fan Zhou 002 (ICASSP, 2022)

Mining Spatio-Temporal Relations via Self-Paced Graph Contrastive Learning. - Rongfan Li; Ting Zhong; Xinke Jiang; Goce Trajcevski; Jin Wu 002; Fan Zhou 002 (KDD, 2022)

Detecting Runtime Exceptions by Deep Code Representation Learning with Attention-Based Graph Neural Networks. - Rongfan Li; Bihuan Chen 001; Fengyi Zhang; Chao Sun; Xin Peng 001 (SANER, 2022)

Landslide Displacement Prediction via Attentive Graph Neural Network. - Ping Kuang; Rongfan Li; Ying Huang; Jin Wu 002; Xucheng Luo; Fan Zhou 002 (Remote. Sens., 2022)

High Detectivity of PbS Films Deposited on Quartz Substrates: The Role of Enhanced Photogenerated Carrier Separation. - Quanjiang Lv; Rongfan Li; Liangchao Fan; Zhi Huang; Zhenyu Huan; Mingyang Yu; Haohua Li 004; Guiwu Liu; Guanjun Qiao; Junlin Liu (Sensors, 2023)

Learning Spatiotemporal Manifold Representation for Probabilistic Land Deformation Prediction. - Xovee Xu; Ting Zhong; Fan Zhou 002; Rongfan Li; Goce Trajcevski; Qinggang Meng (IEEE Trans. Cybern., 2024)