Rongfang Li

Mining Spatio-Temporal Relations via Self-Paced Graph Contrastive Learning

Goce Trajcevski, Fan Zhou, Ting Zhong, 2022, KDD.

A Probabilistic Framework for Land Deformation Prediction (Student Abstract)

Goce Trajcevski, Fan Zhou, Kunpeng Zhang, 2022, AAAI.

Dynamic Manifold Learning for Land Deformation Forecasting

Goce Trajcevski, Fan Zhou, Kunpeng Zhang, 2022, AAAI.

Landslide Displacement Prediction via Attentive Graph Neural Network

Xucheng Luo, Y. Huang, Rongfang Li, 2022, Remote. Sens..

Land Deformation Prediction via Slope-Aware Graph Neural Networks

Fan Zhou, Goce Trajcevski, Kunpeng Zhang, 2021, AAAI Conference on Artificial Intelligence.

A hybrid code representation learning approach for predicting method names

Bihuan Chen, Xin Peng, Fengyi Zhang, 2021, J. Syst. Softw..

Detecting Runtime Exceptions by Deep Code Representation Learning with Attention-Based Graph Neural Networks

Bihuan Chen, Chao Sun, Xin Peng, 2022, 2022 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER).

Learning Spatiotemporal Manifold Representation for Probabilistic Land Deformation Prediction

Goce Trajcevski, Fan Zhou, Ting Zhong, 2023, IEEE Transactions on Cybernetics.

CeO2 nanorods decorated In2O3 nanoparticles for enhanced low temperature detection of hydrogen

Yunhao Qu, Rongfang Li, Mingyang Yu, 2023, Inorganic Chemistry Communications.

Mining Spatio-Temporal Relations via Self-Paced Graph Contrastive Learning

Goce Trajcevski, Fan Zhou, Ting Zhong, 2022, KDD.