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C. Eze

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#machine learning Preprint Sep 2026

SETTer: Sparse-Encoder Transformer for Long-term Multivariate Time Series Forecasting

SETTer is introduced, a transformer-based model that addresses challenges of long-term multivariate time series forecasting by incorporating novel techniques for decoupled self-attention and hybrid masking and outperforms state-of-the-art models in 88% of the scenarios.

Abraham Ezema, C. Eze, F. Ponci et al. · 0 citations

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