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[ascl:2208.025] Yonder: Data denoising and reconstruction

YONDER uses singular value decomposition to perform low-rank data denoising and reconstruction. It takes a tabular data matrix and an error matrix as input and returns a denoised version of the original dataset as output. The approach enables a more accurate data analysis in the presence of uncertainties. Consequently, this package can be used as a simple toolbox to perform astronomical data cleaning.

Code site:
https://pypi.org/project/yonder/ https://github.com/pengchzn/yonder
Used in:
https://ui.adsabs.harvard.edu/abs/2022arXiv220211472C
Described in:
https://ui.adsabs.harvard.edu/abs/2022RNAAS...6...51C
Bibcode:
2022ascl.soft08025C

Views: 2912

ascl:2208.025
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