Abstract: Financial time series prediction is an important and challenging data mining task for quantitative investment. The inherent non-linearity, high noise, and susceptibility to various factors, ...
Abstract: Recent studies have revealed the significant potential of spatiotemporal graph neural networks for multivariate time series forecasting with missing values. These methods typically represent ...
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