2 papers
astro-ph.IM2021
Benchmarking and Scalability of Machine Learning Methods for Photometric Redshift Estimation
Ben Henghes, Connor Pettitt, Jeyan Thiyagalingam +2
Obtaining accurate photometric redshift estimations is an important aspect of cosmology, remaining a prerequisite of many analyses. In creating novel methods to produce redshift es…
astro-ph.EP2020
Machine Learning for Searching the Dark Energy Survey for Trans-Neptunian Objects
B. Henghes, O. Lahav, D. W. Gerdes +56
In this paper we investigate how implementing machine learning could improve the efficiency of the search for Trans-Neptunian Objects (TNOs) within Dark Energy Survey (DES) data wh…