most citedA Mathematical Introduction to Generative Adversarial Nets (GAN)

15 citations · 38 across the 4 of their papers we have counts for

collaborators

6 papers

cs.LG202015 cited

A Mathematical Introduction to Generative Adversarial Nets (GAN)

Yang Wang

Generative Adversarial Nets (GAN) have received considerable attention since the 2014 groundbreaking work by Goodfellow et al. Such attention has led to an explosion in new ideas,…

cs.LG2020

Advbox: a toolbox to generate adversarial examples that fool neural networks

Dou Goodman, Hao Xin, Wang Yang +3

In recent years, neural networks have been extensively deployed for computer vision tasks, particularly visual classification problems, where new algorithms reported to achieve or…

cs.HC201914 cited

Deck.gl: Large-scale Web-based Visual Analytics Made Easy

Yang Wang

In this paper, we demonstrate how deck.gl, an open-source project born out of data-heavy visual analytics applications, has grown into the robust visualization framework it is toda…

stat.ML2019

Optimal low rank tensor recovery

Jian-Feng Cai, Lizhang Miao, Yang Wang +1

We investigate the sample size requirement for exact recovery of a high order tensor of low rank from a subset of its entries. In the Tucker decomposition framework, we show that t…

cs.LG20195 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.LG20194 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…