36 citations · 46 across the 3 of their papers we have counts for
Showing 2024Show all
2 papers · 1 filter
astro-ph.CO2024★ 10 cited
: A generative, fast, and differentiable halo model for wide-field galaxy surveys
Simon Ding, Guilhem Lavaux, Jens Jasche
Mock halo catalogues are indispensable data products for developing and validating cosmological inference pipelines. A major challenge in generating mock catalogues is modelling th…
astro-ph.IM2024★ 36 cited
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…