StratLearn-z: Improved photo-$z$ estimation from spectroscopic data subject to selection effects
A precise measurement of photometric redshifts (photo-z) is crucial for the success of modern photometric galaxy surveys. Machine learning (ML) methods show great promise in this context, but suffer from covariate shift in training sets due to selection bias where interesting sources, e.g., high red...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Maynooth Academic Publishing
2025-05-01
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| Series: | The Open Journal of Astrophysics |
| Online Access: | https://doi.org/10.33232/001c.137525 |
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