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[Research Article] Uncertainty quantification in geospatial AI/ML applications: methods, metrics, and open-source support with an air quality use case

Spatial distribution of PurpleAir (triangles) and EPA (squares) sensors across California, shown in relation to major cities LULC classes. The adoption of AI/ML models in geospatial applications faces ...
Nature

Conformal Prediction Methods in Uncertainty Quantification

Conformal prediction provides a nonparametric framework for generating statistically valid prediction intervals or sets under minimal assumptions. At its core is the calibration of model outputs ...
Nature

Uncertainty Quantification in Deep Learning for Medical Imaging

Uncertainty quantification integrates methods that measure the confidence of deep learning predictions in medical imaging, addressing both intrinsic data noise and model limitations. In clinical ...