ScholarGate
Assistent
Machine learningDeep Learning, Time Series Forecasting, Foundation Models

TimeGPT

TimeGPT er en grundmodel for tidsserier introduceret af Garza og White i 2023, der forener prognoser, anomalidetektion og klassificering i en enkelt fortrænet model. Inspireret af store sprogmodeller er TimeGPT fortrænet på diverse tidsserier og overføres godt til nedstrømsopgaver med minimal finjustering.

Åbn i MethodMindSnartVideoSnartDownload slides

Læs hele metoden

Kun for medlemmer

Log ind med en gratis konto for at læse dette afsnit.

Log ind

Method map

The neighbourhood of related methods — select a node to explore.

Kilder

  1. Garza, F., & White, C. W. (2023). TimeGPT-1: A Time Series Foundation Model. In ICML 2024 Time Series Workshop. link

Sådan citerer du denne side

ScholarGate. (2026, June 3). A Time Series Foundation Model. ScholarGate. https://scholargate.app/da/deep-learning/timegpt

Which method?

Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.

Compare side by side

Refereret af

ScholarGateTimeGPT (A Time Series Foundation Model). Hentet 2026-06-15 fra https://scholargate.app/da/deep-learning/timegpt · Datasæt: https://doi.org/10.5281/zenodo.20539026