13 citations · 31 across the 15 of their papers we have counts for
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astro-ph.IM2024
COmoving Computer Acceleration (COCA): -body simulations in an emulated frame of reference
Deaglan J. Bartlett, Marco Chiarenza, Ludvig Doeser +1
-body simulations are computationally expensive, so machine-learning (ML)-based emulation techniques have emerged as a way to increase their speed. Although fast, surrogate mode…
astro-ph.IM2024
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…