Deconstructing Generative Adversarial Networks

27 January 2019

Papers citing "Deconstructing Generative Adversarial Networks"

9 / 9 papers shown

Title
Fundamental Limits of Deep Learning-Based Binary Classifiers Trained with Hinge Loss T. Getu Georges Kaddoum M. Bennis 40 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 36 0 0 26 Nov 2022
Pursuit of a Discriminative Representation for Multiple Subspaces via Sequential Games Druv Pai Michael Psenka Chih-Yuan Chiu Manxi Wu Yan Sun Y. Ma 24 6 0 18 Jun 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 98 30 0 24 May 2022
Optimal oracle inequalities for solving projected fixed-point equations Wenlong Mou A. Pananjady Martin J. Wainwright 18 14 0 09 Dec 2020
Robust estimation via generalized quasi-gradients Banghua Zhu Jiantao Jiao Jacob Steinhardt 23 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 26 818 0 20 Jan 2020
Conditional Image Synthesis With Auxiliary Classifier GANs Augustus Odena C. Olah Jonathon Shlens GAN 250 3,190 0 30 Oct 2016
Limit laws of the empirical Wasserstein distance: Gaussian distributions Thomas Rippl Axel Munk A. Sturm 52 64 0 15 Jul 2015