On gradient regularizers for MMD GANs

29 May 2018

Papers citing "On gradient regularizers for MMD GANs"

22 / 22 papers shown

Title
Learning Deep Kernels for Non-Parametric Independence Testing Nathaniel Xu Feng Liu Danica J. Sutherland BDL 31 0 0 10 Sep 2024
Deep MMD Gradient Flow without adversarial training Alexandre Galashov Valentin De Bortoli Arthur Gretton DiffM 37 7 0 10 May 2024
Stability Analysis Framework for Particle-based Distance GANs with Wasserstein Gradient Flow Chuqi Chen Yue Wu Yang Xiang GAN 15 0 0 04 Jul 2023
Multi-level Latent Space Structuring for Generative Control Oren Katzir Vicky Perepelook Dani Lischinski Daniel Cohen-Or 19 4 0 11 Feb 2022
Variational Wasserstein gradient flow JiaoJiao Fan Qinsheng Zhang Amirhossein Taghvaei Yongxin Chen 72 54 0 04 Dec 2021
The Geometric Occam's Razor Implicit in Deep Learning Benoit Dherin Micheal Munn David Barrett 22 6 0 30 Nov 2021
RoMA: Robust Model Adaptation for Offline Model-based Optimization Sihyun Yu Sungsoo Ahn Le Song Jinwoo Shin OffRL 16 31 0 27 Oct 2021
Adversarially Robust Kernel Smoothing Jia-Jie Zhu Christina Kouridi Yassine Nemmour Bernhard Schölkopf 21 7 0 16 Feb 2021
A case for new neural network smoothness constraints Mihaela Rosca T. Weber A. Gretton S. Mohamed AAML 25 48 0 14 Dec 2020
On the Convergence of Gradient Descent in GANs: MMD GAN As a Gradient Flow Youssef Mroueh Truyen V. Nguyen 26 25 0 04 Nov 2020
Blindness of score-based methods to isolated components and mixing proportions Wenliang K. Li Heishiro Kanagawa 13 34 0 23 Aug 2020
Estimating Barycenters of Measures in High Dimensions Samuel N. Cohen Michael Arbel M. Deisenroth 15 22 0 14 Jul 2020
Learning Deep Kernels for Non-Parametric Two-Sample Tests Feng Liu Wenkai Xu Jie Lu Guangquan Zhang A. Gretton Danica J. Sutherland 16 176 0 21 Feb 2020
Smoothness and Stability in GANs Casey Chu Kentaro Minami Kenji Fukumizu GAN 21 56 0 11 Feb 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
On Computation and Generalization of Generative Adversarial Imitation Learning Minshuo Chen Yizhou Wang Tianyi Liu Zhuoran Yang Xingguo Li Zhaoran Wang T. Zhao 33 40 0 09 Jan 2020
Statistical Inference for Generative Models with Maximum Mean Discrepancy François‐Xavier Briol Alessandro Barp Andrew B. Duncan Mark Girolami 21 70 0 13 Jun 2019
Maximum Mean Discrepancy Gradient Flow Michael Arbel Anna Korba Adil Salim A. Gretton 24 158 0 11 Jun 2019
Learning Implicit Generative Models by Matching Perceptual Features Cicero Nogueira dos Santos Youssef Mroueh Inkit Padhi Pierre L. Dognin GAN 23 28 0 04 Apr 2019
High-Fidelity Image Generation With Fewer Labels Mario Lucic Michael Tschannen Marvin Ritter Xiaohua Zhai Olivier Bachem Sylvain Gelly GAN OOD 31 157 0 06 Mar 2019
Deep Generative Learning via Variational Gradient Flow Yuan Gao Yuling Jiao Yang Wang Yao Wang Can Yang Shunkang Zhang 19 36 0 24 Jan 2019
Interaction Matters: A Note on Non-asymptotic Local Convergence of Generative Adversarial Networks Tengyuan Liang J. Stokes 27 211 0 16 Feb 2018