[2603.20352] The Multiverse of Time Series Machine Learning: an Archive for Multivariate Time Series Classification

Computer Science > Machine Learning arXiv:2603.20352 (cs) [Submitted on 20 Mar 2026] Title:The Multiverse of Time Series Machine Learning: an Archive for Multivariate Time Series Classification Authors:Matthew Middlehurst, Aiden Rushbrooke, Ali Ismail-Fawaz, Maxime Devanne, Germain Forestier, Angus Dempster, Geoffrey I. Webb, Christopher Holder, Anthony Bagnall View a PDF of the paper titled The Multiverse of Time Series Machine Learning: an Archive for Multivariate Time Series Classification, by Matthew Middlehurst and 8 other authors View PDF HTML (experimental) Abstract:Time series machine learning (TSML) is a growing research field that spans a wide range of tasks. The popularity of established tasks such as classification, clustering, and extrinsic regression has, in part, been driven by the availability of benchmark datasets. An archive of 30 multivariate time series classification datasets, introduced in 2018 and commonly known as the UEA archive, has since become an essential resource cited in hundreds of publications. We present a substantial expansion of this archive that more than quadruples its size, from 30 to 133 classification problems. We also release preprocessed versions of datasets containing missing values or unequal length series, bringing the total number of datasets to 147. Reflecting the growth of the archive and the broader community, we rebrand it as the Multiverse archive to capture its diversity of domains. The Multiverse archive includes datase...