Robust Machine Learning Applied to Astronomical Data Sets. II. Quantifying Photometric Redshifts for Quasars Using Instance‐based Learning

Author:

Ball Nicholas M.,Brunner Robert J.,Myers Adam D.,Strand Natalie E.,Alberts Stacey L.,Tcheng David,Llora Xavier

Publisher

American Astronomical Society

Subject

Space and Planetary Science,Astronomy and Astrophysics

Cited by 45 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Measuring photometric redshifts for high-redshift radio source surveys;Publications of the Astronomical Society of Australia;2023

2. Machine learning applications in astrophysics: Photometric redshift estimation;FIRST INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE & DATA ANALYTICS: Incorporating the 1st South-East Asia Workshop on Computational Physics and Data Analytics (CPDAS 2021);2023

3. Galaxy Spectra Neural Networks (GaSNets). I. Searching for Strong Lens Candidates in eBOSS Spectra Using Deep Learning;Research in Astronomy and Astrophysics;2022-05-26

4. Estimating galaxy redshift in radio-selected datasets using machine learning;Astronomy and Computing;2022-04

5. Photometric redshift estimation of BASS DR3 quasars by machine learning;Monthly Notices of the Royal Astronomical Society;2021-11-10

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