TabPFN and top tree-based models reach threat scores of about 0.62 to 0.64 for post-wildfire debris-flow prediction, with rainfall intensity and storm accumulation the most important features, and synthetic data augmentation helps most models.
and Addison, Priscilla and Oommen, Thomas and Salazar, Sean E
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Evaluating Machine Learning Models for Post-Wildfire Debris-Flow Prediction
TabPFN and top tree-based models reach threat scores of about 0.62 to 0.64 for post-wildfire debris-flow prediction, with rainfall intensity and storm accumulation the most important features, and synthetic data augmentation helps most models.