Uncertainty Quantification in Reduced‐Order Gas‐Phase Atmospheric Chemistry Modeling Using Ensemble SINDy

Lin Guo, Xiaokai Yang, Zhonghua Zheng, Nicole Riemer, Christopher W. Tessum

Research output: Contribution to journal › Article › peer-review

Original language	English
Journal	Journal of Geophysical Research: Machine Learning and Computation
DOIs	https://doi.org/10.1029/2024JH000358
Publication status	Published - Dec 2024

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title = "Uncertainty Quantification in Reduced‐Order Gas‐Phase Atmospheric Chemistry Modeling Using Ensemble SINDy",

author = "Lin Guo and Xiaokai Yang and Zhonghua Zheng and Nicole Riemer and Tessum, {Christopher W.}",

year = "2024",

month = dec,

doi = "10.1029/2024JH000358",

language = "English",

journal = "Journal of Geophysical Research: Machine Learning and Computation",

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publisher = "John Wiley & Sons Ltd",

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T1 - Uncertainty Quantification in Reduced‐Order Gas‐Phase Atmospheric Chemistry Modeling Using Ensemble SINDy

AU - Guo, Lin

AU - Yang, Xiaokai

AU - Zheng, Zhonghua

AU - Riemer, Nicole

AU - Tessum, Christopher W.

PY - 2024/12

Y1 - 2024/12

UR - https://doi.org/10.1029/2024JH000358

U2 - 10.1029/2024JH000358

DO - 10.1029/2024JH000358

M3 - Article

SN - 2993-5210

JO - Journal of Geophysical Research: Machine Learning and Computation

JF - Journal of Geophysical Research: Machine Learning and Computation

ER -