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Fast Point Spread Function Modeling with Deep Learning
We find that our approach is able to accurately reproduce the SDSS PSF at the pixel level, which, due to the speed of both the model evaluation and the parameter estimation, offers good prospects for incorporating our method into the $MCCL$ framework.
Accelerating Approximate Bayesian Computation with Quantile Regression: Application to Cosmological Redshift Distributions
This model is trained on a small number of simulations and estimates which regions of the prior space are likely to be accepted into the posterior.
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