JeremyChou28/MTSCI
The official source code of MTSCI: A Conditional Diffusion Model for Consistent Imputation in Incomplete Time Series
This tool helps data analysts and researchers fill in missing data points within complex, interconnected time series datasets. It takes incomplete multivariate time series data, such as sensor readings or economic indicators, and generates plausible, consistent values for the gaps. This ensures a complete and reliable dataset for further analysis or model training.
No commits in the last 6 months.
Use this if you need to accurately complete multivariate time series data that has gaps or missing observations, ensuring the imputed values are consistent with the overall trends and relationships.
Not ideal if you only have simple, univariate time series data or if you need to forecast future values rather than fill in historical gaps.
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34
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Language
Python
License
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Last pushed
Apr 26, 2025
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