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Adaptively temporal graph convolution model for epidemic prediction of multiple age groups

  • Published:2021-08 Issue: Volume: Page:
  • ISSN:2667-3258
  • Container-title:Fundamental Research
  • language:en
  • Short-container-title:Fundamental Research

Author:

Wang Yuejiao,Zeng Dajun Daniel,Zhang Qingpeng,Zhao Pengfei,Wang Xiaoli,Wang Quanyi,Luo Yin,Cao Zhidong

Funder

Beijing Natural Science Foundation

Beijing Nova Program

National Natural Science Foundation of China

Publisher

Elsevier BV

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Graph Contrastive Learning with Node-Level Accurate Difference;Fundamental Research;2024-09

2. A Review of Graph Neural Networks in Epidemic Modeling;Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining;2024-08-24

3. AI for science: Predicting infectious diseases;Journal of Safety Science and Resilience;2024-06

4. Prediction of Covid-19 confirmed cases and deaths using hybrid support vector machine-Taguchi method;Computers & Industrial Engineering;2024-05

5. Forecasting infections with spatio-temporal graph neural networks: a case study of the Dutch SARS-CoV-2 spread;Frontiers in Physics;2023-12-14
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