3 papers
Cosmo-Learn: code for learning cosmology using different methods and mock data
Reginald Christian Bernardo, Daniela Grandón, Jackson Levi Said +3
We present cosmo_learn, an open-source python-based software package designed to simulate cosmological data and perform data-driven inference using a range of modern statistical an…
Classifying galaxies in the Galaxy10 DECals dataset using Inception and Residual CNNs
Lanz Anthonee A. Lagman, Prospero C. Naval, Reinabelle C. Reyes
Image data regarding galactic morphology is expected to increase both in quantity and quality for the next foreseeable years; thus it is important to explore which deep learning ar…
Nature-inspired optimization, the Philippine Eagle, and cosmological parameter estimation
Reginald Christian Bernardo, Erika Antonette Enriquez, Renier Mendoza +2
Precise and accurate estimation of cosmological parameters is crucial for understanding the Universe's dynamics and addressing cosmological tensions. In this methods paper, we expl…