Zhe-Hao Liang

Local Overfitting in Machine Learning Models Drives Spatially Uneven Performance in Atmospheric Observations

Atmospheric and environmental monitoring relies on observation networks with highly uneven spatial density, yet machine-learning models trained on such networks prioritize data-dense regions, producing systematic uneven accuracy precisely where reliable predictions are most needed. Existing fairness methods from ma...