Representational aspects of depth and conditioning in normalizing flows

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Abstract:

Normalizing flows are among the most popular paradigms in generative modeling, especially for images, primarily because we can efficiently evaluate the likelihood of a data point. Normalizing flows also come with difficulties: models which produce good samples typically need to be extremely deep -- which comes with accompanying vanishin...More

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