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Arxiv
1d
19
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DeformTime: Capturing Variable Dependencies with Deformable Attention for Time Series Forecasting
- DeformTime is a neural network architecture for multivariable time series (MTS) forecasting.
- It uses deformable attention blocks (DABs) to capture correlated temporal patterns and improve prediction accuracy.
- DeformTime performs well on various MTS data sets, outperforming previous methods and reducing mean absolute error by 7.2% on average.
- The architecture shows consistent performance gains across longer forecasting horizons.
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