7 citations · 7 across the 2 of their papers we have counts for
4 papers · 1 filter
Pre-trained Forecasting Models: Strong Zero-Shot Feature Extractors for Time Series Classification
Andreas Auer, Daniel Klotz, Sebastinan Böck +1
Recent research on time series foundation models has primarily focused on forecasting, leaving it unclear how generalizable their learned representations are. In this study, we exa…
Chronos-2: From Univariate to Universal Forecasting
Abdul Fatir Ansari, Oleksandr Shchur, Jaris Küken +20
Pretrained time series models have enabled inference-only forecasting systems that produce accurate predictions without task-specific training. However, existing approaches largely…
Zero-Shot Time Series Forecasting with Covariates via In-Context Learning
Andreas Auer, Raghul Parthipan, Pedro Mercado +5
Pretrained time series models, capable of zero-shot forecasting, have demonstrated significant potential in enhancing both the performance and accessibility of time series forecast…
TiRex: Zero-Shot Forecasting Across Long and Short Horizons with Enhanced In-Context Learning
Andreas Auer, Patrick Podest, Daniel Klotz +3
In-context learning, the ability of large language models to perform tasks using only examples provided in the prompt, has recently been adapted for time series forecasting. This p…