I took a quick look because I'm aware of the work that has gone in to producing the best estimates of \Lambda CDM parameters from CMB data. This has been done

I took a quick look because I'm aware of the work that has gone in to producing the best estimates of \Lambda CDM parameters from CMB data. This has been done by large-scale MCMC - not DL at all. But, the CMB signal really is Gaussian, so MCMC is well-suited. By going to the trouble of making a principled forward model including error statistics, you get error bars on all reported parameters, such as the age of the universe - these error bars are critical to later analysis. ("This model requires a Hubble constant in the range ... which is not supported by current observational evidence.") Parameter estimation from large scale structure is not as "easy". OTOH, I wonder about the accuracy of their map from (cosmological parameters) -> (Large scale structure), because that's what their system is inverting. That is, I wonder about their training data. From sec. 4C of the current paper, and comparing to their reference to Ravanbakhsh et al 2017 (ICML, [1]), they seem to be using numerical simulations (N-body sims representing gravitational coalescence). These models might have large systematic errors, and their inverse may have its own problems. Long way to say: I wonder how these estimates of Lambda CDM parameters are viewed by the astrophysics community? The present paper is more of a systems/methods paper than an astrophysics paper. The estimates will come with no error bars, and will be critically based on the simulations used, and the NN limitations. [1] https://arxiv.org/pdf/1711.02033.pdf https://arxiv.org/pdf/1711.02033.pdf