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Time Weaver: A Conditional Time Series Generation Model
March 6, 2024, 5:41 a.m. | Sai Shankar Narasimhan, Shubhankar Agarwal, Oguzhan Akcin, Sujay Sanghavi, Sandeep Chinchali
cs.LG updates on arXiv.org arxiv.org
Abstract: Imagine generating a city's electricity demand pattern based on weather, the presence of an electric vehicle, and location, which could be used for capacity planning during a winter freeze. Such real-world time series are often enriched with paired heterogeneous contextual metadata (weather, location, etc.). Current approaches to time series generation often ignore this paired metadata, and its heterogeneity poses several practical challenges in adapting existing conditional generation approaches from the image, audio, and video domains …
abstract arxiv capacity city cs.lg current demand eess.sp electric electricity electric vehicle etc imagine location metadata planning series time series type weather world
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