Kolmogorov backward equations are a set of differential equations that describe the evolution of probabilities in a Markov process over time. These equations provide a mathematical framework for predicting the future behavior of a stochastic process based on its current state and the transition rates between states. They are essential for understanding how probability distributions change in systems governed by Markov chains, linking current and future states through their transition dynamics.
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