Kullback–Leibler Divergence: Theory, Applications, and Implications

Kullback–Leibler divergence (KL divergence), also known as relative entropy, is a fundamental concept in statistics and information theory. It measures how one probability distribution diverges from a second, reference probability distribution. This article delves into the mathematical foundations of KL divergence, its interpretation, properties, applications across various fields, and practical considerations for its implementation. 1. Introduction