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InfoGAN: Interpretable Representation Learning by ...
One class of such methods trains a subset of the representation to match the supplied label using supervised learning: bilinear models [21] separate style and content; multi-view perceptron [22] separate face identity and view point; and Yang et al. [23] developed a recurrent variant that generates a sequence of latent factor transformations.
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arXiv:0706.3639v1 [cs.AI] 25 Jun 2007
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InfoGAN: Interpretable Representation Learning by ...
papers.nips.ccOne class of such methods trains a subset of the representation to match the supplied label using supervised learning: bilinear models [18] separate style and content; multi-view perceptron [19] separate face identity and view point; and Yang et al. [20] developed a recurrent variant that generates a sequence of latent factor transformations.