4 papers · 1 filter
GREAT: Generalizable Representation Enhancement via Auxiliary Transformations for Zero-Shot Environmental Prediction
Shiyuan Luo, Chonghao Qiu, Runlong Yu +2
Environmental modeling faces critical challenges in predicting ecosystem dynamics across unmonitored regions due to limited and geographically imbalanced observation data. This cha…
Learning to Retrieve for Environmental Knowledge Discovery: An Augmentation-Adaptive Self-Supervised Learning Framework
Shiyuan Luo, Runlong Yu, Chonghao Qiu +5
The discovery of environmental knowledge depends on labeled task-specific data, but is often constrained by the high cost of data collection. Existing machine learning approaches u…
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…
Physics-Guided Foundation Model for Scientific Discovery: An Application to Aquatic Science
Runlong Yu, Chonghao Qiu, Robert Ladwig +3
Physics-guided machine learning (PGML) has become a prevalent approach in studying scientific systems due to its ability to integrate scientific theories for enhancing machine lear…