380 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- H'ector J. Hort'ua2 profiles4 · h 3
- Héctor J. Hortúa2 profiles4 · h 6
- W. Herrera4 · h 12
- Shirley Gómez Páez3 profiles3 · h 3
- Carlos Eduardo Maldonado2 · h 7
- J. E. García-Farieta2 · h 3
- P. Burset2 · h 21
- Alfredo Levy Yeyati1 · h 4
- Andrés Mora‐Valencia1 · h 13
- A. Yeyati1 · h 41
- Camilo Martínez1 · h 3
- Cecilia Murrugarra1 · h 6
- Universidad Nacional de ColombiaCO8 papers
- Escuela Colombiana de Ingenieria Julio GaravitoCO4 papers
- Aalto UniversityFI2 papers
- Instituto de Astrofísica de CanariasES2 papers
- Liverpool John Moores UniversityGB2 papers
- Universidad Autónoma de MadridES2 papers
- Universidad de La LagunaES2 papers
- Universidad de Los AndesCO2 papers
- Abington Memorial HospitalUS1 paper
- Adler PlanetariumUS1 paper
- Ben-Gurion University of the NegevIL1 paper
- Boğaziçi UniversityTR1 paper
4 papers · 1 filter
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…
The NANOGrav 15-year Data Set: Constraints on Supermassive Black Hole Binaries from the Gravitational Wave Background
Gabriella Agazie, Akash Anumarlapudi, Anne M. Archibald +111
The NANOGrav 15-year data set shows evidence for the presence of a low-frequency gravitational-wave background (GWB). While many physical processes can source such low-frequency gr…
About Jordan and Einstein frames: a study in inflationary magnetogenesis
Joel Velásquez, Héctor J. Hortua, Leonardo Castañeda
There has been considerable interest in the community to understand if the Einstein and Jordan frames are either physically equivalent to each other or if there exists a preference…
Constraining cosmological parameters from N-body simulations with Variational Bayesian Neural Networks
Héctor J. Hortúa, Luz Ángela García, Leonardo Castañeda C
Methods based on Deep Learning have recently been applied on astrophysical parameter recovery thanks to their ability to capture information from complex data. One of these methods…