Test of artificial neural networks in likelihood-free cosmological constraints: A comparison of information maximizing neural networks and denoising autoencoder-Reference-Cited by-同舟云学术

Test of artificial neural networks in likelihood-free cosmological constraints: A comparison of information maximizing neural networks and denoising autoencoder

Published:2023-03-13 Issue:6 Volume:107 Page:
ISSN:2470-0010
Container-title:Physical Review D
language:en
Short-container-title:Phys. Rev. D

Author:

Chen Jie-Feng,Wang Yu-Chen,Zhang Tingting,Zhang Tong-Jie^ORCID

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

Publisher

American Physical Society (APS)

Link

http://harvest.aps.org/v2/journals/articles/10.1103/PhysRevD.107.063517/fulltext

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1. The Complete Light-curve Sample of Spectroscopically Confirmed SNe Ia from Pan-STARRS1 and Cosmological Constraints from the Combined Pantheon Sample

2. Measurements ofH(z) andDA(z) from the two-dimensional two-point correlation function of Sloan Digital Sky Survey luminous red galaxies

3. Uniqueness of twisted linear periods and twisted Shalika periods

4. Approximate Bayesian Computation for astronomical model analysis: a case study in galaxy demographics and morphological transformation at high redshift

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