Generative models are a type of machine learning model that can generate new data instances that resemble the training data. They learn the underlying probability distribution of the training data and then sample from that distribution to create new data. Common uses include generating realistic images, text, audio, and other types of data. Some popular examples include Variational Autoencoders (VAEs), Generative Adversarial Networks (GANs), and autoregressive models.
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