Improving Stock Trend Prediction with Multi-granularity Denoising Contrastive Learning

Author:

Wang Mingjie1,Chen Feng2,Guo Jianxiong3,Jia Weijia3

Affiliation:

1. BNU-HKBU United International College,Department of Computer Science,Zhuhai,China

2. The University of Adelaide,Department of Computer Science,Adelaide,Australia

3. Advanced Institute of Natural Sciences, Beijing Normal University,Zhuhai,China

Publisher

IEEE

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. MP3Net:Multi-scale Patch Parallel Prediction Networks for Multivariate Time Series Forecasting;2024 International Joint Conference on Neural Networks (IJCNN);2024-06-30

2. Research on Stock Prediction Model using Mode Decomposition Algorithm and Support Vector Regression;Proceedings of the 2024 Guangdong-Hong Kong-Macao Greater Bay Area International Conference on Digital Economy and Artificial Intelligence;2024-01-19

3. Multi-Granularity Spatio-Temporal Correlation Networks for Stock Trend Prediction;IEEE Access;2024

4. Improving stock trend prediction with pretrain multi-granularity denoising contrastive learning;Knowledge and Information Systems;2023-12-28

5. An Online Multi-Item Auction With Differential Privacy in Edge-Assisted Blockchains;IEEE Internet of Things Journal;2023

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