270 citations · 709 across the 23 of their papers we have counts for
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astro-ph.EP2019★ 35 cited
Realistic On-The-Fly Outcomes of Planetary Collisions: Machine Learning Applied to Simulations of Giant Impacts
Saverio Cambioni, Erik Asphaug, Alexandre Emsenhuber +3
Planet formation simulations are capable of directly integrating the evolution of hundreds to thousands of planetary embryos and planetesimals, as they accrete pairwise to become p…
astro-ph.EP2019★ 22 cited
Constraining the Thermal Properties of Planetary Surfaces using Machine Learning: Application to Airless Bodies
Saverio Cambioni, Marco Delbo, Andrew J. Ryan +2
We present a new method for the determination of the surface properties of airless bodies from measurements of the emitted infrared flux. Our approach uses machine learning techniq…