2 citations · 2 across the 10 of their papers we have counts for
3 papers · 1 filter
FMTK: A Modular Toolkit for Composable Time Series Foundation Model Pipelines
Hetvi Shastri, Pragya Sharma, Walid A. Hanafy +2
Foundation models (FMs) have opened new avenues for machine learning applications due to their ability to adapt to new and unseen tasks with minimal or no further training. Time-se…
Spectral Predictability as a Fast Reliability Indicator for Time Series Forecasting Model Selection
Oliver Wang, Pengrui Quan, Kang Yang +1
Practitioners deploying time series forecasting models face a dilemma: exhaustively validating dozens of models is computationally prohibitive, yet choosing the wrong model risks p…
CarbonX: An Open-Source Tool for Computational Decarbonization Using Time Series Foundation Models
Diptyaroop Maji, Kang Yang, Prashant Shenoy +2
Computational decarbonization aims to reduce carbon emissions in computing and societal systems such as data centers, transportation, and built environments. This requires accurate…