A novel approach called Bi-Mamba4TS, integrating the state space model with a bidirectional architecture, enhances long-term predictive accuracy in time series forecasting. It utilizes patching techniques to capture evolutionary patterns with finer granularity and outperforms traditional and newer forecasting methods in various datasets.
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