A curated 142-billion-point real-world multivariate time series corpus improves zero-shot forecasting when combined with existing synthetic and univariate pretraining data across four foundation models.
Temporal fusion transformers for inter- pretable multi-horizon time series forecasting.International Journal of Forecasting, 37(4):1748–1764, 2021
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RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models
A curated 142-billion-point real-world multivariate time series corpus improves zero-shot forecasting when combined with existing synthetic and univariate pretraining data across four foundation models.