SE3D trains a Bayesian neural network on libraries of 3D dust radiative transfer toy models to emulate spectral energy distributions and structural parameters for fitting resolved galaxy observations.
Figure A1.Validation of model predicting whether a toy model galaxy is physical or unphysical, as evaluated on an unseen testing set
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SE3D: Building a radiative transfer emulator to fit panchromatic resolved galaxy observations with 3D models of dust and stars
SE3D trains a Bayesian neural network on libraries of 3D dust radiative transfer toy models to emulate spectral energy distributions and structural parameters for fitting resolved galaxy observations.