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[ascl:2206.005] NonnegMFPy: Nonnegative Matrix Factorization with heteroscedastic uncertainties and missing data

NonnegMFPy solves nonnegative matrix factorization (NMF) given a dataset with heteroscedastic uncertainties and missing data with a vectorized multiplicative update rule; this can be used create a mask and iterate the process to exclude certain new data by updating the mask. The code can work on multi-dimensional data, such as images, if the data are first flattened to 1D.

Code site:
https://github.com/guangtunbenzhu/NonnegMFPy
Used in:
https://ui.adsabs.harvard.edu/abs/2018ApJ...866...36L
Described in:
https://ui.adsabs.harvard.edu/abs/2016arXiv161206037Z
Bibcode:
2022ascl.soft06005Z

Views: 1352

ascl:2206.005
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