arXiv AI June 4, 2026 By Jonas Petersen, Gian-Alessandro Lombardi, Riccardo Maggioni, Camilla Mazzoleni, Federico Martelli, Philipp Petersen

HEPA: A Self-Supervised Horizon-Conditioned Event Predictive Architecture for Time Series

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arXiv:2605. 11130v4 Announce Type: replace-cross Abstract: Critical events in multivariate time series, from turbine failures to cardiac arrhythmias, demand accurate prediction, yet labeled data is scarce because such events are rare and costly to annotate.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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Tabby: An Open Pretraining Recipe for Time Series Foundation Models

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