• Corpus ID: 249018222

Balanced Graph Structure Learning for Multivariate Time Series Forecasting

@inproceedings{Chen2022BalancedGS,
  title={Balanced Graph Structure Learning for Multivariate Time Series Forecasting},
  author={Weijun Chen and Yanze Wang and Chengshuo Du and Zhenglong Jia and Feng Liu and Ran Chen},
  year={2022}
}
. Accurate forecasting of multivariate time series is an extensively studied subject in finance, transportation, and computer science. Fully mining the correlation and causation between the variables in a multivariate time series exhibits noticeable results in improving the performance of a time series model. Recently, some models have explored the dependencies between variables through end-to-end graph structure learning without the need for predefined graphs. However, current models do not… 

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References

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