Friday, June 27th
COLOURS
AstroStatistics Summer School
Scale 1 (~7arcmin)
Scale 2 (~14arcmin)
Scale 1 (~7arcmin)
Multiscale
Friday, May 16th
pyro_mcmc
Pyro
enables flexible and expressive deep probabilistic modeling, unifying the best of modern deep learning and Bayesian modeling
Scale 1 (~7arcmin)
Scale 2 (~14arcmin)
Scale 1 (~7arcmin)
Multiscale
Friday, March 7th
Investigate the same thing within an ILI framework → no need for covmat, allows to investigate bias in a more proper way, allows for use of other statistics (e.g. NN-based statistics)
Develop a new mass-mapping method based on Plug-and-Play that provides a fast reconstruction with uncertainty quantification and is trained once
Plug-and-Play → framework that allows to combine deep denoising algorithms with optimization algorithms to solve inverse problems
Some nice results for KappaTNG with a simple U-Net denoiser
Train on cosmoSLICS:
Idea - Explore two things:
This will show: