Robust Time Series Contrastive Representation Learning via Explicit Seasonal-Trend Disentanglement
We address universal self-supervised representation learning for time series under label scarcity and distribution shifts. A key challenge is that prevalent encode-then-decompose pipelines only implicitly separate seasonal and trend signals, which mixes noise across components and degrades robustnes...
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| Principais autores: | , |
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| Format: | Artigo |
| Sprog: | Inglês |
| Udgivet: |
IEEE
2025-01-01
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| Serier: | IEEE Access |
| Fag: | |
| Online adgang: | https://ieeexplore.ieee.org/document/11202913/ |
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