36 citations · 71 across the 12 of their papers we have counts for
3 papers · 1 filter
Learning the Universe: Cosmological and Astrophysical Parameter Inference with Galaxy Luminosity Functions and Colours
Christopher C. Lovell, Tjitske Starkenburg, Matthew Ho +9
We perform the first direct cosmological and astrophysical parameter inference from the combination of galaxy luminosity functions and colours using a simulation based inference ap…
On the Significance of Rare Objects at High Redshift: The Impact of Cosmic Variance
Christian Kragh Jespersen, Charles L. Steinhardt, Rachel S. Somerville +1
The discovery of extremely luminous galaxies at ultra-high redshifts () has challenged galaxy formation models. Most analyses of this tension have not accounted for the…
LtU-ILI: An All-in-One Framework for Implicit Inference in Astrophysics and Cosmology
Matthew Ho, Deaglan J. Bartlett, Nicolas Chartier +12
This paper presents the Learning the Universe Implicit Likelihood Inference (LtU-ILI) pipeline, a codebase for rapid, user-friendly, and cutting-edge machine learning (ML) inferenc…