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Found 5 papers, 1 papers with code
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
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
Deep Learning for space-variant deconvolution in galaxy surveys
Deconvolution of large survey images with millions of galaxies requires to develop a new generation of methods which can take into account a space variant Point Spread Function (PSF) and have to be at the same time accurate and fast.
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
Convergent ADMM Plug and Play PET Image Reconstruction
In this work, we investigate hybrid PET reconstruction algorithms based on coupling a model-based variational reconstruction and the application of a separately learnt Deep Neural Network operator (DNN) in an ADMM Plug and Play framework.
