1 citations · 1 across the 2 of their papers we have counts for
3 papers
Zero-shot Forecasting by Simulation Alone
Boris N. Oreshkin, Mayank Jauhari, Ravi Kiran Selvam +10
Zero-shot time-series forecasting holds great promise, but is still in its infancy, hindered by limited and biased data corpora, leakage-prone evaluation, and privacy and licensing…
A More Realistic Evaluation of Cross-Frequency Transfer Learning and Foundation Forecasting Models
Kin G. Olivares, Malcolm Wolff, Tatiana Konstantinova +8
Cross-frequency transfer learning (CFTL) has emerged as a popular framework for curating large-scale time series datasets to pre-train foundation forecasting models (FFMs). Althoug…
SPADE-S: A Sparsity-Robust Foundational Forecaster
Malcolm Wolff, Matthew Li, Ravi Kiran Selvam +11
Despite significant advancements in time series forecasting, accurate modeling of time series with strong heterogeneity in magnitude and/or sparsity patterns remains challenging fo…