52 citations · 418 across the 59 of their papers we have counts for
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stat.ML2019★ 1 cited
A stochastic alternating minimizing method for sparse phase retrieval
Jianfeng Cai, Yuling Jiao, Xiliang Lu +1
Sparse phase retrieval plays an important role in many fields of applied science and thus attracts lots of attention. In this paper, we propose a \underline{sto}chastic alte\underl…
cs.LG2019★ 5 cited
Wasserstein-Wasserstein Auto-Encoders
Shunkang Zhang, Yuan Gao, Yuling Jiao +3
To address the challenges in learning deep generative models (e.g.,the blurriness of variational auto-encoder and the instability of training generative adversarial networks, we pr…
cs.LG2019★ 4 cited
Deep Generative Learning via Variational Gradient Flow
Yuan Gao, Yuling Jiao, Yang Wang +3
We propose a general framework to learn deep generative models via \textbf{V}ariational \textbf{Gr}adient Fl\textbf{ow} (VGrow) on probability spaces. The evolving distribution tha…