Sign inGet started
Dataset · Hugging Face

ChengsenWang/CGTSF

CGTSF: Context-Guided Time Series Forecasting ✨ Introduction The context-guided time series forecasting task entails the transformation of text into time series data. Relevant multimodal datasets are limited. To address these data gaps, we have collected three multimodal datasets that offer valuable resources for future research. The following table summarizes the statistics of these datasets. MSPG comprises 13 months of solar power generation data on 27… See the full description on the dataset page: https://huggingface.co/datasets/ChengsenWang/CGTSF.

Author / organizationChengsenWang
License (as declared)apache-2.0
Downloads152 (as reported by Hugging Face)
Likes0
Created8 July 2024
Last updated at source17 December 2024
time-seriestime-series-forecastingmultimodalitymultimodal-time-seriescontext-guided-time-series-forecasting
Embed this entry
<iframe src="https://silytics.si/embed/item/6040fc68-94f6-42d2-b8e3-25b7e7fa0e9d" width="420" height="190" style="border:0" loading="lazy" title="Silytics entry"></iframe>

Free, no tracking. More about feeds and embeds.

Recent changes

  • 16 Oct 2026 Description: CGTSF: Context-Guided Time Series Forecasting ✨ Introduction The context-guided time series forecasting task entails the transformation of text into time series data. Relevant multimodal datasets are limited. To address these data gaps, we → CGTSF: Context-Guided Time Series Forecasting ✨ Introduction The context-guided time series forecasting task entails the transformation of text into time series data. Relevant multimodal datasets are limited. To address these data gaps, we

Changes detected by Silytics between refreshes of the source.

More from ChengsenWang

Silytics shows public metadata from Hugging Face and links to the original. Information may be incomplete or out of date. Last refreshed 16 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.