sparse-forecasting

This paper proposes TA-SparseMG, a lightweight cross-period forecasting model for long-term time series that incorporates trend-aware reversible instance normalization, scale-adaptive gated denoising, and a multiscale gated-attention MLP module to address nonstationarity and high-frequency disturbances.