1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.LG2026
CAAL: Confidence-Aware Active Learning for Heteroscedastic Atmospheric Regression
Fei Jiang, Jiyang Xia, Junjie Yu +6
Quantifying the impacts of air pollution on health and climate relies on key atmospheric particle properties such as toxicity and hygroscopicity. However, these properties typicall…
physics.comp-ph2024★ 1 cited
Uncertainty Quantification in Reduced-Order Gas-Phase Atmospheric Chemistry Modeling using Ensemble SINDy
Lin Guo, Xiaokai Yang, Zhonghua Zheng +2
Uncertainty quantification during atmospheric chemistry modeling is computationally expensive as it typically requires a large number of simulations using complex models. As large-…