Inference of the physical properties of stellar populations from observed photometry and
spectroscopy is a key goal in the study of galaxy evolution. In recent years, the quality and …

We present CosmoPower, a suite of neural cosmological power spectrum emulators
providing orders-of-magnitude acceleration for parameter estimation from two-point statistics …

We use luminous red galaxies selected from the imaging surveys that are being used for
targeting by the Dark Energy Spectroscopic Instrument (DESI) in combination with CMB …

We introduce a novel approach to boost the efficiency of the importance nested sampling
(INS) technique for Bayesian posterior and evidence estimation using deep learning. Unlike …

With just a month of data, JWST is already transforming our view of the universe, revealing
and resolving starlight in unprecedented populations of galaxies. Although" HST-dark" …

We present pop-cosmos: a comprehensive model characterizing the galaxy population,
calibrated to 140,938 (r< 25 selected) galaxies from the Cosmic Evolution Survey …

Bayesian parameter inference is an essential tool in modern cosmology, and typically
requires the calculation of 10 5–10 6 theoretical models for each inference of model …

We present a forward-modeling framework for estimating galaxy redshift distributions from
photometric surveys. Our forward model is composed of: a detailed population model …

The advent of the James Webb Space Telescope (JWST) signals a new era in exploring
galaxies in the high-z universe. Current and upcoming JWST imaging will potentially detect …

State-of-the-art spectral energy distribution (SED) analyses use a Bayesian framework to
infer the physical properties of galaxies from observed photometry or spectra. They require …