Machine learningTime-series forecasting

TSMixer: All-MLP Architecture for Time Series Forecasting

TSMixer is a multivariate time-series forecasting model introduced by Si-An Chen and colleagues at Google in 2023. It challenges the prevailing dominance of Transformer-based architectures by demonstrating that a simple stack of interleaved MLP layers — alternating between mixing along the time axis and mixing across feature channels — achieves strong forecasting accuracy while remaining computationally efficient and easy to interpret architecturally.

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Sources

  1. Chen, S.-A., Li, C.-L., Yoder, N., Arik, S. O., & Pfister, T. (2023). TSMixer: An all-MLP architecture for time series forecasting. Transactions on Machine Learning Research. link

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Referenced by

ScholarGateTSMixer (TSMixer (All-MLP Architecture for Forecasting)). Retrieved 2026-06-04 from https://scholargate.app/en/deep-learning/tsmixer