A 1D CNN trained on over a million synthetic Earth-analog spectra retrieves gas abundances and planet properties in seconds, with Monte Carlo Dropout uncertainties.
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Towards the Habitable Worlds Observatory: 1D CNN Retrieval of Reflection Spectra from Evolving Earth Analogs
A 1D CNN trained on over a million synthetic Earth-analog spectra retrieves gas abundances and planet properties in seconds, with Monte Carlo Dropout uncertainties.