Non-Parametric Reconstruction of Cosmological Observables Using Gaussian Processes Regression

Non-Parametric Reconstruction of Cosmological Observables Using Gaussian Processes Regression

The current accelerated expansion of the Universe remains one of the most intriguing topics in modern cosmology, driving the search for innovative statistical techniques. Recent advancements in machine learning have significantly enhanced its application across various scientific fields, including p...

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Bibliographic Details
Main Authors: José de Jesús Velázquez, Luis A. Escamilla, Purba Mukherjee, J. Alberto Vázquez
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Universe
Subjects:
cosmology
dark energy
Hubble parameter
deceleration parameter
linear regression
gaussian process
Online Access:https://www.mdpi.com/2218-1997/10/12/464
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