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Found 4 papers, 3 papers with code
Physics simulation capabilities of LLMs
Physics and coding errors are the most common, with some unnecessary or insufficient lines.
A machine-generated catalogue of Charon's craters and implications for the Kuiper belt
This is motivated by the recent results of Singer et al. (2019) who, using manual cataloging, found a change in the size distribution slope of craters smaller than 12 km in diameter, translating into a paucity of small Kuiper Belt objects.
Automated crater shape retrieval using weakly-supervised deep learning
Manual validation of a subset of these "new" craters indicates that a majority of them are real, which we take as an indicator of the strength of our model in learning to identify craters, despite incomplete training data.
Lunar Crater Identification via Deep Learning
Crater counting on the Moon and other bodies is crucial to constrain the dynamical history of the Solar System.
Earth and Planetary Astrophysics
