M5

The 'M5' dataset is a large-scale benchmark for time series forecasting that contains sales data from thousands of products across various categories, used to evaluate the performance of forecasting models.

Papers using M5 (12)

Foundation Models for Demand Forecasting via Dual-Strategy Ensembling2025 · 3 citesAME-TS: Anchored Mixture-of-Experts for Time Series Forecasting2026Time-Aware Prior Fitted Networks for Zero-Shot Forecasting with Exogenous Variables2026Let Experts Feel Uncertainty: A Multi-Expert Label Distribution Approach to Probabilistic Time Series Forecasting2026Faithful and Interpretable Explanations for Complex Ensemble Time Series Forecasts using Surrogate Models and Forecastability Analysis2025Hierarchical Time Series Forecasting Via Latent Mean Encoding2025Deep Learning for Time Series Forecasting: Tutorial and Literature Survey2020 · 345 citesTSMixer: An All-MLP Architecture for Time Series Forecasting2023 · 122 citesHierarchical Proxy Modeling for Improved HPO in Time Series Forecasting2022 · 2 citesPastprop-RNN: improved predictions of the future by correcting the past2021Hierarchical Forecasting at Scale2023Scalable Probabilistic Forecasting in Retail with Gradient Boosted Trees: A Practitioner's Approach2023