most citedData-driven modeling of rotation curves with artificial neural networks

1 citations · 1 across the 2 of their papers we have counts for

collaborators

5 papers

astro-ph.IM2026

Modeling Doppler Shifts in Radial-Velocity Data with Deep Learning toward Earth-mass Exoplanet Detection

Isidro Gómez-Vargas, Xavier Dumusque, Yinan Zhao +2

Detecting the tiny Doppler shifts induced by Earth-mass planets in stellar radial-velocity measurements remains extremely challenging due to stellar activity. Many deep-learning me…

astro-ph.GA20261 cited

Data-driven modeling of rotation curves with artificial neural networks

Gabriela Garcia-Arroyo, Isidro Gómez-Vargas, J. Alberto Vázquez

Galactic rotation curves are crucial for understanding the distribution of mass in galaxies. Despite advances in precision observations, there are discrepancies between the inferre…

astro-ph.IM2024

Deep Learning and genetic algorithms for cosmological Bayesian inference speed-up

Isidro Gómez-Vargas, J. Alberto Vázquez

In this paper, we present a novel approach to accelerate the Bayesian inference process, focusing specifically on the nested sampling algorithms. Bayesian inference plays a crucial…

astro-ph.CO2024

Exploring the Evolution of Nonlinear Electrodynamics in the Universe: A Dynamical Systems Approach

Ricardo García-Salcedo, Isidro Gómez-Vargas, Tame González +2

This paper investigates the dynamics of cosmological models incorporating nonlinear electrodynamics (NLED), focusing on their stability and causality. We explore two specific NLED…

astro-ph.EP2024

Improving Earth-like planet detection in radial velocity using deep learning

Yinan Zhao, Xavier Dumusque, Michael Cretignier +9

Many novel methods have been proposed to mitigate stellar activity for exoplanet detection as the presence of stellar activity in radial velocity (RV) measurements is the current m…