NEST improves long-term multivariate forecasting under dataset-level distribution shifts by clustering regimes in moment-entropy space and recomposing specialized variate-attention experts via a content-plus-geometry router.
A comparison of arima and lstm in forecasting time series
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NEST: Tackling Dataset-Level Distribution Shifts via Regime-Oriented Mixture-of-Experts
NEST improves long-term multivariate forecasting under dataset-level distribution shifts by clustering regimes in moment-entropy space and recomposing specialized variate-attention experts via a content-plus-geometry router.