SPaRSe-TIME introduces a decomposition of time series into saliency-projected low-rank components that delivers competitive accuracy with lower computation and explicit interpretability.
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SPaRSe-TIME: Saliency-Projected Low-Rank Temporal Modeling for Efficient and Interpretable Time Series Prediction
SPaRSe-TIME introduces a decomposition of time series into saliency-projected low-rank components that delivers competitive accuracy with lower computation and explicit interpretability.