Understanding the Limitations of Conditional Generative Models

ICLR 2020 Ethan FetayaJörn-Henrik JacobsenWill GrathwohlRichard Zemel

Class-conditional generative models hold promise to overcome the shortcomings of their discriminative counterparts. They are a natural choice to solve discriminative tasks in a robust manner as they jointly optimize for predictive performance and accurate modeling of the input distribution... (read more)

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