mlsanityData to 7 Oct 2026

SDMixer: Sparse Dual-Mixer for Time Series Forecasting

arXiv 2602.23581 ↗First posted 27 Feb 2026cs.LG cs.AIcited by 0

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Abstract (arXiv)

Multivariate time series forecasting is widely applied in fields such as transportation, energy, and finance. However, the data commonly suffers from issues of multi-scale characteristics, weak correlations, and noise interference, which limit the predictive performance of existing models. This paper proposes a dual-stream sparse Mixer prediction framework that extracts global trends and local dynamic features from sequences in both the frequency and time domains, respectively. It employs a sparsity mechanism to filter out invalid information, thereby enhancing the accuracy of cross-variable dependency modeling. Experimental results demonstrate that this method achieves leading performance on multiple real-world scenario datasets, validating its effectiveness and generality. The code is available at https://github.com/SDMixer/SDMixer

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 15 of its 26 references that are in the map. First posted on arXiv 27 Feb 2026.

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References · 15

  1. 2017Attention Is All You Needcited by 59,932
  2. 2022A Time Series is Worth 64 Words: Long-term Forecasting with Transformerscited by 1,981
  3. 2021Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecastingcited by 1,654
  4. 2021MLP-Mixer: An all-MLP Architecture for Visioncited by 1,441
  5. 2022FEDformer: Frequency Enhanced Decomposed Transformer for Long-term Series Forecastingcited by 1,200
  6. 2018Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognitioncited by 1,199
  7. 2022TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysiscited by 1,030
  8. 2023iTransformer: Inverted Transformers Are Effective for Time Series Forecastingcited by 906
  9. 2019Graph WaveNet for Deep Spatial-Temporal Graph Modelingcited by 820
  10. 2021CSDI: Conditional Score-based Diffusion Models for Probabilistic Time Series Imputationcited by 577
  11. 2021SCINet: Time Series Modeling and Forecasting with Sample Convolution and Interactioncited by 335
  12. 2024TimeMixer: Decomposable Multiscale Mixing for Time Series Forecastingcited by 333
3 more
  1. 2023TSMixer: Lightweight MLP-Mixer Model for Multivariate Time Series Forecastingcited by 136
  2. 2024TimeMixer++: A General Time Series Pattern Machine for Universal Predictive Analysiscited by 113
  3. 2023TimeGNN: Temporal Dynamic Graph Learning for Time Series Forecastingcited by 4

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