R. Quinn Thomas

Advancing Near-Term Water Quality Forecasting with Explainable Machine Learning and Probabilistic Uncertainty Quantification

Abstract Phytoplankton blooms threaten drinking-water security, yet translating high-frequency monitoring data into timely, reliable, and interpretable forecasts remains challenging. Machine learning (ML) models can improve predictive accuracy but typically require intensive tuni...