Machine learningTime-series forecasting

Chronos: A Tokenized Foundation Model for Time-Series Forecasting

Chronos is a family of pre-trained probabilistic forecasting models introduced by Ansari et al. at Amazon in 2024. It adapts the language-model paradigm to time series by quantizing continuous values into discrete tokens, enabling a standard transformer to be trained on a large heterogeneous corpus of time-series data. The result is a zero-shot forecasting model that generalizes across domains without requiring dataset-specific retraining.

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Sources

  1. Ansari, A. F., Stella, L., Turkmen, C., Zhang, X., Mercado, P., Shen, H., et al. (2024). Chronos: Learning the language of time series. Transactions on Machine Learning Research. link

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Referenced by

ScholarGateChronos (Chronos (Tokenized Time-Series Foundation Model)). Retrieved 2026-06-04 from https://scholargate.app/en/deep-learning/chronos