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TiRex

TiRex is a pretrained zero-shot time-series forecasting model introduced in 2025 by the NX-AI xLSTM team (Auer et al.). Built on the Extended Long Short-Term Memory (xLSTM) architecture, TiRex is trained at scale on diverse time-series corpora and can forecast unseen datasets without any fine-tuning. Its core idea is to exploit enhanced in-context learning: the model reads the entire available history as a context and produces forecasts for both short and long horizons directly from that context.

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TiRex (xLSTM-based Zero-Shot Forecasting Model)

Taxonomický záznam metódy · ml-model / deep-learning

Auer, A., Podest, P., Klotz, D., Böck, S., Klambauer, G., & Hochreiter, S. (2025). TiRex: Zero-shot forecasting across long and short horizons with enhanced in-context learning. arXiv preprint. · URL

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Taxonomic bucketChronosmachine-suggested · Relational suggestion, not evidence.Same method familyLSTMmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketTimesFMmachine-suggested · Relational suggestion, not evidence.