3 papers
cs.LG2026
CHAM-net: A Contrastive Hierarchical Adaptive Meta-network for Robust Global Methane Flux Prediction
Rongchao Dong, Yiming Sun, Shuo Chen +4
Methane is a potent greenhouse gas that significantly contributes to global warming. However, accurately estimating global methane emissions and consumption remains challenging due…
cs.LG2026
X-MethaneWet: A Cross-scale Global Wetland Methane Emission Benchmark Dataset for Advancing Science Discovery with AI
Yiming Sun, Shuo Chen, Shengyu Chen +9
Methane (CH) is the second most powerful greenhouse gas after carbon dioxide and plays a crucial role in climate change due to its high global warming potential. Accurately mod…
cs.LG2026
Role-Aware Conditional Inference for Spatiotemporal Ecosystem Carbon Flux Prediction
Yiming Sun, Runlong Yu, Rongchao Dong +6
Accurate prediction of terrestrial ecosystem carbon fluxes (e.g., CO, GPP, and CH) is essential for understanding the global carbon cycle and managing its impacts. However,…