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Cooperative Training of Fast Thinking Initializer and Slow Thinking Solver for Conditional Learning
[article]
2021
arXiv
pre-print
This paper studies the problem of learning the conditional distribution of a high-dimensional output given an input, where the output and input may belong to two different domains, e.g., the output is a photo image and the input is a sketch image. We solve this problem by cooperative training of a fast thinking initializer and slow thinking solver. The initializer generates the output directly by a non-linear transformation of the input as well as a noise vector that accounts for latent
arXiv:1902.02812v3
fatcat:yb5aq6rzlvho3mc3p7yfznndja