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Rongfan Li 中文版 Currently, Rongfan Li is a second-year Master student at University of Electronic Science and Technology of China (UESTC), supervised by Prof. Fan Zhou and Prof. Ting Zhong. His research interests include but not limit to Graph Neural Network, Spatio-temporal Forecasting, Data Mining and Mutual Information. Email: rongfanli1998@gmail.com Phone: (+86)13183802787 Others: Github | Resume in PDF |
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Land Deformation Prediction via Slope-Aware Graph Neural Networks, Download Fan Zhou, Rongfan Li, Goce Trajcevski, Kunpeng Zhang AAAI 2021, The Thirty-Fifth AAAI Conference on Artificial Intelligence (CCF-A) Time: 2020.12.2, Accept rate: 21.4%=1692/7911, Score: 8666 Keywords: Graph Neural Network, Manifold Learning, and Spatio-temporal We introduce a slope-aware graph neural network (SA-GNN) to leverage continuously monitored data and predict the land displacement. |
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Dynamic Manifold Learning for Land Deformation Forecasting, Download Fan Zhou, Rongfan Li, Qiang Gao, Goce Trajcevski, Kunpeng Zhang, Ting Zhong AAAI 2022, The Thirty-Sixth AAAI Conference on Artificial Intelligence (CCF-A) Time: 2021.12.1, Accept rate: 15.0%=1349/9020, Score: 8876 Keywords: Normalizing Flow, Manifold Learning, Neural ODE and Spatio-temporal We present DyLand - Dynamic Manifold Learning with Normalizing Flows for Land deformation prediction – a novel framework for learning dynamic structures of terrain surface and improving the performance of land deformation prediction. |
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一种基于时空注意力克里金的边坡形变数据插值方法, Download 黎嵘繁, 钟婷, 吴劲, 周帆, 匡平 计算机科学 (CCF-B), Time: 2021.8.10 Keywords: 时空数据挖掘, 时空注意力, 克里金, 山体滑坡 |
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A Probabilistic Framework for Land Deformation Prediction, Download Rongfan Li, Fan Zhou, Goce Trajcevski, Kunpeng Zhang, Ting Zhong AAAI 2022 poster, The Thirty-Sixth AAAI Conference on Artificial Intelligence (CCF-A) Time: 2021.11.6 Keywords: Normalizing Flow, Variational Inference and Spatio-temporal |
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Probabilistic Fine-Grained Urban Flow Inference with Normalizing Flow, Download Ting Zhong, Haoyang Yu, Rongfan Li, Xovee Xu, Xucheng Luo, and Fan Zhou ICASSP 2022, The International Conference on Acoustics, Speech, & Signal Processing (CCF-B) Time: 2022.1.22 Keywords: Spatio-temporal, Urban Flow and Normalizing Flow |
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(UNDER REVIEW) Mining Spatio-Temporal ... KDD 2022, 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (CCF-A) |
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(UNDER REVIEW) GNN-based Spatio-Temporal Manifold Learning: An Application of Landslide Prediction TKDE, IEEE Transactions on Knowledge and Data Engineering (CCF-A) |
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(UNDER REVIEW) Landslide Displacement Prediction via Attentive Graph Neural Network Remote Sensing, 中科院2区Top |
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Understanding VAE and Normalizing Flows, Download My notes about VAE and Normalizing Flows. |