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Background: What is a Generative Model? | Google

More formally, given a set of data instances X and a set of labels Y:

  • Generative models capture the joint probability p(X, Y), or just p(X) if there are no labels.
  • Discriminative models capture the conditional probability p(Y | X).

A generative model includes the distribution of the data itself, and tells you how likely a given example is. For example, models that predict the next word in a sequence are typically generative models (usually much simpler than GANs) because they can assign a probability to a sequence of words.


  • Generative models can generate new data instances.
  • Discriminative models discriminate between different kinds of data instances.

Deep Generative Modeling


Generative Modeling Language