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[ascl:2411.011] MMLPhoto-z: Cross-modal contrastive learning method for estimating photo-z of quasars

MMLPhoto-z estimates the photo-z of quasars using a cross-modal contrastive learning approach. This method employs adversarial training and contrastive loss functions to promote the mutual conversion between multi-band photometric data features (magnitude, color) and photometric image features, while extracting modality-invariant features. MMLPhoto-z can also be applied to tasks like photo-z estimation for galaxies with missing magnitudes. Overall, this method proves effective in enhancing the photo-z estimation across diverse datasets and conditions.

Code site:
https://github.com/Valar-hub/MMLPhoto-z
Described in:
https://ui.adsabs.harvard.edu/abs/2024AJ....168..244Z
Bibcode:
2024ascl.soft11011Z

Views: 523

ascl:2411.011
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