Mathematics, Linear Algebra, Machine Learning, Data Science.
through probabilistic layers. Cholesky Decomposition is used in these models to efficiently compute the gradients with respect to the model parameters. We’ll see in a later chapter how these decompisitions also have applications in stochastics and probability theory, particularly in the context of