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Found 6 papers, 2 papers with code
Shear measurement bias II: a fast machine learning calibration method
The method estimates the individual shear responses of the objects from the combination of several measured properties on the images using supervised learning.
Cosmology and Nongalactic Astrophysics Instrumentation and Methods for Astrophysics
Heuristics for Efficient Sparse Blind Source Separation
Sparse Blind Source Separation (sparse BSS) is a key method to analyze multichannel data in fields ranging from medical imaging to astrophysics.
A highly precise shear bias estimator independent of the measured shape noise
This shear response is the multiplicative shear bias for each image.
Cosmology and Nongalactic Astrophysics
Unsupervised feature-learning for galaxy SEDs with denoising autoencoders
In addition, preliminary results illustrate that this enables the capturing of extra physically meaningful information, such as redshift dependence, galaxy mass evolution and variation over the specific star formation rate.
Instrumentation and Methods for Astrophysics Astrophysics of Galaxies
Robust Sparse Blind Source Separation
Blind Source Separation is a widely used technique to analyze multichannel data.
Sparsity and adaptivity for the blind separation of partially correlated sources
Blind source separation (BSS) is a very popular technique to analyze multichannel data.
