Introduction to Deep Evidential Regression for Uncertainty Quantification

# Machine Learning Models Need to Know When They're Guessing Most AI systems confidently give you answers even when they're working with incomplete information—like a student who bluffs their way through an exam. Deep Evidential Regression is a new technique that teaches neural networks to admit uncertainty, flagging when they're unsure so you know which predictions to trust and which to verify. This matters because overconfident AI can lead to costly mistakes in real-world decisions, from medical diagnoses to financial forecasting.