16 citations · 19 across the 3 of their papers we have counts for
3 papers
cs.LG2021★ 2 cited
Wasserstein Generative Learning of Conditional Distribution
Shiao Liu, Xingyu Zhou, Yuling Jiao +1
Conditional distribution is a fundamental quantity for describing the relationship between a response and a predictor. We propose a Wasserstein generative approach to learning a co…
cs.LG2021★ 1 cited
Non-Asymptotic Error Bounds for Bidirectional GANs
Shiao Liu, Yunfei Yang, Jian Huang +2
We derive nearly sharp bounds for the bidirectional GAN (BiGAN) estimation error under the Dudley distance between the latent joint distribution and the data joint distribution wit…
cs.LG2021★ 16 cited
An error analysis of generative adversarial networks for learning distributions
Jian Huang, Yuling Jiao, Zhen Li +3
This paper studies how well generative adversarial networks (GANs) learn probability distributions from finite samples. Our main results establish the convergence rates of GANs und…