Neural network reconstructions for the hubble parameter, growth rate and distance modulus

HIGHLIGHTS

• who: Isidro Gu00f3mez-Vargas from the ICF, Universidad Nacional Autu00f3noma de Mu00e9xico, Cuernavaca, Morelos, Mexico have published the paper: Neural network reconstructions for the Hubble parameter, growth rate and distance modulus, in the Journal: Eur. Phys. J. C
• what: By using neural networks the authors can generate computational models of observational datasets and then the authors compare them with the original ones to verify the consistency of the method . The aim of a nonparametric approach is to infer (reconstruct) an unknown quantity based mainly on the data and make as few assumptions as possible . The . . .
  

   

  

  If you want to have access to all the content you need to log in!

  Thanks :)

  Username or E-mail:

  If you don't have an account, you can create one here.