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Covers ARMA models for time series forecasting, discussing implications, properties of forecast error, challenges with predictions, and covariance models.
Compares gaseous, scintillator, and semiconductor detectors for radiation detection, emphasizing the importance of understanding uncertainties in measurements.
Explores enhancing machine learning predictions by refining error metrics and applying constraints for improved accuracy in electron density predictions.
