arxiv
PublishedMay 22, 2026 at 4:00 AM
—neutral
Dynamic TMoE: A Drift-Aware Dynamic Mixture of Experts Framework for Non-Stationary Time Series Forecasting
Publisher summary· verbatim
arXiv:2605.20678v1 Announce Type: cross Abstract: Non-stationary time series forecasting is challenged by evolving distribution shifts that static models struggle to capture. While Mixture-of-Experts (MoE) architectures offer a promising paradigm for decoupling complex drift patterns, existing appro
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Originally published on arxiv ↗