The multivariate normal distribution has a large number of parameters, $O(n^2 + n)$, which can make optimization challenging. It would be beneficial to have an implementation of the normal distribution with a diagonal covariance matrix, reducing the number of parameters to $2n$. This simplification would make the optimization process more manageable.