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Uncertainty in Machine Learning: Entropy and Conformal Prediction
This chapter explores the relationship between differential equations, real-world applications, and the intersection of conformal prediction with information theory. It emphasizes how understanding uncertainty through concepts like entropy impacts machine learning model reliability and safety. The discussion further delves into conformal training and the integration of side information, illustrating how these approaches enhance predictive accuracy and reduce uncertainty.