Time Series Forecasting
Time-series forecasting exploded in 2023-2025 when foundation models crossed over from NLP. Nixtla's TimeGPT (2023), Google's TimesFM (2024), and Amazon's Chronos showed that a single pretrained model can zero-shot forecast diverse series, rivaling task-specific statistical models like ETS and ARIMA. Yet the Monash benchmark and M-competition lineage (M4, M5) reveal an uncomfortable truth: simple ensembles of statistical methods still win on many univariate tasks. The real battle now is multivariate long-horizon forecasting, where PatchTST and iTransformer compete with state-space models like Mamba.
M4 Competition
100,000 time series from diverse domains (finance, demographic, macro, micro, industry, other). Competition ran in 2018. Lower sMAPE/MASE/OWA is better.
Top 10
Leading models on M4 Competition.
All datasets
6 datasets tracked for this task.
Related tasks
Other tasks in Time Series.
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