10 citations · 17 across the 4 of their papers we have counts for
4 papers
Bayesian Inference of Primordial Magnetic Field Parameters from CMB with Spherical Graph Neural Networks
Juan Alejandro Pinto Castro, Héctor J. Hortúa, Jorge Enrique García-Farieta +1
Deep learning has emerged as a transformative methodology in modern cosmology, providing powerful tools to extract meaningful physical information from complex astronomical dataset…
Parameter sensitivity of cosmic pairwise velocities in the non-linear regime of structure formation
Jorge Enrique García-Farieta, Héctor J. Hortúa
The peculiar velocities of dark matter tracers drive the growth of cosmic structures, providing a sensitive test of cosmological models and strengthening constraints on the nature…
Forecasting VIX using Bayesian Deep Learning
Héctor J. Hortúa, Andrés Mora-Valencia
Recently, deep learning techniques are gradually replacing traditional statistical and machine learning models as the first choice for price forecasting tasks. In this paper, we le…
Bayesian deep learning for cosmic volumes with modified gravity
Jorge Enrique García-Farieta, Héctor J Hortúa, Francisco-Shu Kitaura
The new generation of galaxy surveys will provide unprecedented data allowing us to test gravity at cosmological scales. A robust cosmological analysis of the large-scale structure…