5 citations · 6 across the 2 of their papers we have counts for
2 papers
astro-ph.CO2026★ 1 cited
Towards an optimal extraction of cosmological parameters from galaxy cluster surveys using convolutional neural networks
Iñigo Sáez-Casares, Matteo Calabrese, Davide Bianchi +4
The possibility to constrain cosmological parameters from galaxy surveys using field-level machine learning methods that bypass traditional summary statistics analyses, depends cru…
astro-ph.IM2024★ 5 cited
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…