Deconstructing Generative Adversarial Networks

27 January 2019

Papers citing "Deconstructing Generative Adversarial Networks"

7 / 7 papers shown

Title
Fundamental Limits of Deep Learning-Based Binary Classifiers Trained with Hinge Loss T. Getu Georges Kaddoum M. Bennis 32 1 0 13 Sep 2023
Distribution estimation and change-point estimation for time series via DNN-based GANs Jianya Lu Ying Mo Zhijie Xiao Lihu Xu Qiuran Yao AI4TS 23 0 0 26 Nov 2022
Byzantine-Robust Federated Learning with Optimal Statistical Rates and Privacy Guarantees Banghua Zhu Lun Wang Qi Pang Shuai Wang Jiantao Jiao D. Song Michael I. Jordan FedML 93 30 0 24 May 2022
Robust estimation via generalized quasi-gradients Banghua Zhu Jiantao Jiao Jacob Steinhardt 13 43 0 28 May 2020
A Review on Generative Adversarial Networks: Algorithms, Theory, and Applications Jie Gui Zhenan Sun Yonggang Wen Dacheng Tao Jieping Ye EGVM 26 817 0 20 Jan 2020
Conditional Image Synthesis With Auxiliary Classifier GANs Augustus Odena C. Olah Jonathon Shlens GAN 224 3,190 0 30 Oct 2016
Limit laws of the empirical Wasserstein distance: Gaussian distributions Thomas Rippl Axel Munk A. Sturm 36 64 0 15 Jul 2015