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Presentation | A33G: Data-Driven Methods for Quantifying Atmospheric Composition: Advances in Computation and Statistical Learning II Poster
Poster
A33G-2243: Mapping and Explaining the Global Variability of Power Plant Plume Detectability from Space
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Wed, Dec 17
Board 2243‚ Hall EFG (Poster Hall)
2:15pm - 5:45pm (Central)
NOLA CC
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Ruizhe Huang
Massachusetts Institute of Technology
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Author(s):
Ruizhe Huang
, Massachusetts Institute of Technology
(First Author, Presenting Author)
Sherrie Wang
, Massachusetts Institute of Technology
View Abstract
Scientific Discipline
Atmospheric Sciences
Suggested Itineraries
Machine Learning and AI
Neighborhood
Earth Covering
Type
Poster
I Will Be at My Poster Time
View This Poster
Main Session
Poster
A33G: Data-Driven Methods for Quantifying Atmospheric Composition: Advances in Computation and Statistical Learning II Poster
2:15pm-5:45pm Dec 17 (Central)
Zhen Qu
Discussion
