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.
Constraints on very high energy gamma-ray emission from the Fermi Bubbles with future ground-based experi- ments.Phys
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
astro-ph.HE 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
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.