120 citations · 223 across the 24 of their papers we have counts for
3 papers · 1 filter
Emulating CO Line Radiative Transfer with Deep Learning
Shiqi Su, Frederik De Ceuster, Jaehoon Cha +5
Modelling carbon monoxide (CO) line radiation is computationally expensive for traditional numerical solvers, especially when applied to complex, three-dimensional stellar atmosphe…
Investigating Deep Learning Methods for Obtaining Photometric Redshift Estimations from Images
Ben Henghes, Connor Pettitt, Jeyan Thiyagalingam +2
Knowing the redshift of galaxies is one of the first requirements of many cosmological experiments, and as it's impossible to perform spectroscopy for every galaxy being observed,…
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…