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Machine learning tool demonstrates predictive capabilities for cross sections in H2O collisions, suggesting enhanced modeling methods.
A machine learning tool using an ensemble of neural networks is proposed to predict cross sections of rotational transitions in H 2 O + H 2 O collisions. Bottom right image courtesy of NASA/JPL-Caltech/UMD.
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Mandal et al. (2025) studied this question.
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