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Robustness of Conditional GANs to Noisy Labels
We study the problem of learning conditional generators from noisy label...
11/08/2018 ∙ by Kiran Koshy Thekumparampil, et al. ∙
18
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Generating High-fidelity, Synthetic Time Series Datasets with DoppelGANger
Limited data access is a substantial barrier to data-driven networking r...
09/30/2019 ∙ by Zinan Lin, et al. ∙
16
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InfoGAN-CR: Disentangling Generative Adversarial Networks with Contrastive Regularizers
Training disentangled representations with generative adversarial networ...
06/14/2019 ∙ by Zinan Lin, et al. ∙
3
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PacGAN: The power of two samples in generative adversarial networks
Generative adversarial networks (GANs) are innovative techniques for lea...
12/12/2017 ∙ by Zinan Lin, et al. ∙
0
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