2 papers
cs.LG2026
Revisiting the Generic Transformer: Deconstructing a Strong Baseline for Time Series Foundation Models
Yunshi Wen, Wesley M. Gifford, Chandra Reddy +3
The recent surge in Time Series Foundation Models has rapidly advanced the field, yet the heterogeneous training setups across studies make it difficult to attribute improvements t…
cs.LG2024
Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series
Vijay Ekambaram, Arindam Jati, Pankaj Dayama +5
Large pre-trained models excel in zero/few-shot learning for language and vision tasks but face challenges in multivariate time series (TS) forecasting due to diverse data characte…