Supervised ML models achieve R^2 > 0.90 when mapping multi-frequency radio data to 0.1-10 GeV gamma-ray intensity and attribute high-frequency radio bands to hadronic processes and low-frequency bands to leptonic processes.
Large-Scale Features of the Radio Sky and a Model for Loop I.Galaxies, 6:56, 2018
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Data-driven modeling of Galactic diffuse emission with multi-wavelength observations
Supervised ML models achieve R^2 > 0.90 when mapping multi-frequency radio data to 0.1-10 GeV gamma-ray intensity and attribute high-frequency radio bands to hadronic processes and low-frequency bands to leptonic processes.