CODE SUMMARY
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1. NEDMP: Neural Enhanced Dynamic Message Passing.
a. Fei Gao, Yan Zhang, Jiang Zhang*. Neural Enhanced Dynamic Message Passing. AISTATS (2022). |
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2. PM2.5 GNN.
a. Shuo Wang, Yanran Li, Jiang Zhang, Qingye Meng, Lingwei Meng, Fei Gao. PM2.5-GNN: A Domain Knowledge Enhanced Graph Neural Network For PM2.5 Forecasting; SIGSPATIAL 2020 virtual conference. |
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3. Network Completion from Time Series Data.
a. Menyuan Chen, Yan Zhang, Zhang Zhang, Lun Du, Shuo Wang, Jiang Zhang*. Inferring network structure with unobservable nodes from time series data. Chaos (2022). |
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4. AIDD: Automated Discovery of Interactions and Dynamics.
a. Zhang Yan, Guo Yu, Zhang Zhang, et al. Automated Discovery of Interactions and Dynamics for Large Networked Dynamical Systems[J]. arXiv:2101.00179, 2021. |
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5. GGN: Gumbel-softmax Graph Network.
a. Zhang Zhang, Yi Zhao, Jing Liu, Shuo Wang, Ruyi Tao, Ruyue Xin, Jiang Zhang. A General Deep Learning Framework for Network Reconstruction and Dynamics Learning; Applied Network Science, 4, 110 (2019). |
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1. DeepLinker: Link Prediction by GAT and Their Byproducts.
a. Weiwei Gu, Fei Gao, Xiaodan Lou, Jiang Zhang*. Discovering latent node Information by graph attention network. Scientific Reports 11, 6967 (2021). |
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2. Network Embedding based on Flow Distance.
a. Weiwei Gu, Li Gong, Xiaodan Lou, Jiang Zhang. The Hidden Flow Structure and Metric Space of Network Embedding Algorithms Based on Random Walks; Scientific Reports, 7: 13114 (2017). |
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3. GSO & EvoGSO: Gumbel-softmax based Optimization.
a. Yaoxin Li, Jing Liu, Guozheng Lin, Yueyuan Hou, Muyun Mou, Jiang Zhang. Gumbel-softmax-based optimization: a simple general framework for optimization problems on graphs. Computational Social Networks volume 8, 5 (2021). |
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4. Complex Network Classification.
a. Ruyue Xin, Jiang Zhang, Yitong Shao. Complex Network Classification with Convolutional Neural Network; Tsinghua Science and Technology, Volume 25, Number 4, 2020. |
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1. scCapNet: Capsule Network for Identifying Cell-type Gene Expression.
a. Lifei Wang, Rui Nie, Zeyang Yu, Ruyue Xin, Caihong Zheng, Zhang Zhang, Jiang Zhang, Jun Cai. An interpretable deep-learning architecture of capsule networks for identifying cell-type gene expression programs from single-cell RNA-sequencing data; Nature Machine Intelligence, 2: 693703(2020). |
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2. Mesoscopic Scaling for Cities.
a. Lei Dong, Zhou Huang, Jiang Zhang, Yu Liu. Understanding the mesoscopic scaling patterns within cities; Scientific Reports 10: 21201 (2020). |
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3. A General Python Package for Flow Network Algorithms.
a. flow_network_embedding. |
| 1. Tools for reconstruction methods / dynamics models and data. |
| 2. BNUSSS Toolkit. |
| 3. Flownetwork Python project. |