Generating Samples using Synthetic Multivariate Distributions

The problem I address in this post is generating samples from multivariate distributions, without having any data. Motivation Generative models are capable of generating new data. Unlike discriminative models, which determine the likelihood of an outcome given a set of input features $P(Y|X)$, a generative model learns the joint distribution between variables $P(X,Y)$. In product development, they can be used for various use cases, including imputing missing data (e.g. with conditional models), determining the likelihood of an observed sample, or creating random samples of data. ... Read more