Intro

Mutual Information: $I(X; Y) = H(X) + H(Y) - H(X, Y)$
KL Divergence: $D(p \vert\vert q) = \sum p(x) \log\frac{p(x)}{q(x)}$
- Measures similarity between distributions
- 0 if equal
- Asymmetric
Copula Models: Generates a multivariate model with unpopular marginal probabilities by using a change of variables to convert the original model to a Gaussian model
- Used in economics; normalizing flows is more popular in machine learning