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Rongfan Li
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2020 – today
- 2024
- [j4]Xovee Xu
, Ting Zhong
Learning Spatiotemporal Manifold Representation for Probabilistic Land Deformation Prediction. IEEE Trans. Cybern. 54(1): 572-585 (2024) - 2023
- [j3]Quanjiang Lv
High Detectivity of PbS Films Deposited on Quartz Substrates: The Role of Enhanced Photogenerated Carrier Separation. Sensors 23(20): 8413 (2023) - 2022
- [j2]Ping Kuang, Rongfan Li
Landslide Displacement Prediction via Attentive Graph Neural Network. Remote. Sens. 14(8): 1919 (2022) - [c6]Fan Zhou, Rongfan Li
Dynamic Manifold Learning for Land Deformation Forecasting. AAAI 2022: 4725-4733 - [c5]Rongfan Li, Fan Zhou, Goce Trajcevski, Kunpeng Zhang, Ting Zhong:
A Probabilistic Framework for Land Deformation Prediction (Student Abstract). AAAI 2022: 13001-13002 - [c4]Ting Zhong, Haoyang Yu
Probabilistic Fine-Grained Urban Flow Inference with Normalizing Flows. ICASSP 2022: 3663-3667 - [c3]Rongfan Li
Mining Spatio-Temporal Relations via Self-Paced Graph Contrastive Learning. KDD 2022: 936-944 - [c2]Rongfan Li, Bihuan Chen, Fengyi Zhang, Chao Sun, Xin Peng:
Detecting Runtime Exceptions by Deep Code Representation Learning with Attention-Based Graph Neural Networks. SANER 2022: 373-384 - 2021
- [j1]Fengyi Zhang, Bihuan Chen, Rongfan Li, Xin Peng:
A hybrid code representation learning approach for predicting method names. J. Syst. Softw. 180: 111011 (2021) - [c1]Fan Zhou, Rongfan Li, Goce Trajcevski, Kunpeng Zhang:
Land Deformation Prediction via Slope-Aware Graph Neural Networks. AAAI 2021: 15033-15040
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