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.


Conveners will be contacted by the AGU25 Program Committee with any requests for mergers or edits to proposals. Conveners will be notified of the acceptance of their proposal in mid-June.


Abstract submissions will also open in mid-June and the deadline for abstract submissions is 30 July, 2025.


Please visit the AGU25 website for more information or please contact AGU with any questions.

Abstract: PyKGML: A Python Library for Efficient Development and Benchmark of Knowledge-Guided Machine Learning for Greenhouse Gas Modeling (AGU25)

PyKGML: A Python Library for Efficient Development and Benchmark of Knowledge-Guided Machine Learning for Greenhouse Gas Modeling

Yufeng Yang1, An Min1, Gavin McNicol2, Chongwei Chen3, Zhenong Jin1,4, Vipin Kumar3 and Licheng LIU1, (1)University of Minnesota Twin Cities, Department of Bioproducts and Biosystems Engineering, Saint Paul, United States, (2)University of Illinois Chicago, Department of Earth and Environmental Sciences, Chicago, United States, (3)University of Minnesota Twin Cities, Department of Computer Science & Engineering, Minneapolis, United States, (4)Peking University, The Institute of Ecology, College of Urban and Environmental Science, Beijing, China
<< Previous Abstract | Next Abstract >>