23 citations · 28 across the 4 of their papers we have counts for
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cs.LG2019★ 23 cited
FCC-GAN: A Fully Connected and Convolutional Net Architecture for GANs
Sukarna Barua, Sarah Monazam Erfani, James Bailey
Generative Adversarial Networks (GANs) are a powerful class of generative models. Despite their successes, the most appropriate choice of a GAN network architecture is still not we…
cs.LG2019★ 5 cited
Quality Evaluation of GANs Using Cross Local Intrinsic Dimensionality
Sukarna Barua, Xingjun Ma, Sarah Monazam Erfani +2
Generative Adversarial Networks (GANs) are an elegant mechanism for data generation. However, a key challenge when using GANs is how to best measure their ability to generate reali…