Flow-based Deep Generative Models
Read OriginalThis technical article explores flow-based deep generative models, a class of models that explicitly learn the probability density function of data using normalizing flows. It contrasts them with GANs and VAEs, detailing their advantages for tasks like data generation and density estimation. The content includes a primer on necessary mathematical concepts like Jacobian determinants and the change of variable rule.
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