ST-MTM shows that masking seasonal and trend components separately, with a contrastive alignment loss, improves self-supervised time series forecasting.
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ST-MTM: Masked Time Series Modeling with Seasonal-Trend Decomposition for Time Series Forecasting
ST-MTM shows that masking seasonal and trend components separately, with a contrastive alignment loss, improves self-supervised time series forecasting.