The deadline to submit a session, town hall, or pre-conference workshop proposal for AGU25 has passed. Please search for and review proposed sessions below. Please note this site is frozen as of 4/29/25 and will not reflect any changes to proposals made after this date.


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Abstract: Deep Learning-based Probabilistic Imaging of Yellowstone’s Hydrothermal System from AEM Data (AGU25)

Deep Learning-based Probabilistic Imaging of Yellowstone’s Hydrothermal System from AEM Data

Chenyu Zhou, University of Houston, Houston, TX, United States, Sihong Wu, University of Houston, Department of Earth and Atmospheric Sciences, Houston, TX, United States, Jiajia Sun, University of Houston, Department of Earth and Atmospheric Sciences, Houston, United States, Jiefu Chen, University of Houston, Electrical and Computer Engineering, Houston, United States and Yueqin Huang, University of Houston, Department of Information Science Technology, Houston, United States