Estimate prior and deduce posterior
데이터의 분포를 학습하여 생성 규칙을 파악
can compute how probable any given model instance is
Can be learned using images from just a single category
Generative models aim to Density Estimation of data
Generate new data from a posterior distribution that is as similar as possible to the distribution of training data. Then we can address better concern on unseen data
