Training generative neural networks via Maximum Mean Discrepancy optimization

14 May 2015

Gintare Karolina Dziugaite

Papers citing "Training generative neural networks via Maximum Mean Discrepancy optimization"

50 / 125 papers shown

Title
On the Convergence of Gradient Descent in GANs: MMD GAN As a Gradient Flow Youssef Mroueh Truyen V. Nguyen 29 25 0 04 Nov 2020
Rescuing neural spike train models from bad MLE Diego M. Arribas Yuan Zhao Il Memming Park 37 8 0 23 Oct 2020
GANs with Variational Entropy Regularizers: Applications in Mitigating the Mode-Collapse Issue Pirazh Khorramshahi Hossein Souri Ramalingam Chellappa S. Feizi GAN DRL 30 4 0 24 Sep 2020
Generative models with kernel distance in data space Szymon Knop Marcin Mazur Przemysław Spurek Jacek Tabor Igor T. Podolak GAN SyDa 27 11 0 15 Sep 2020
Estimating Barycenters of Measures in High Dimensions Samuel N. Cohen Michael Arbel M. Deisenroth 26 22 0 14 Jul 2020
Modeling Lost Information in Lossy Image Compression Yaolong Wang Mingqing Xiao Chang-Shu Liu Shuxin Zheng Tie-Yan Liu 32 23 0 22 Jun 2020
Reparameterized Variational Divergence Minimization for Stable Imitation Dilip Arumugam Debadeepta Dey Alekh Agarwal Asli Celikyilmaz E. Nouri W. Dolan 33 3 0 18 Jun 2020
Exploring the Vulnerability of Deep Neural Networks: A Study of Parameter Corruption Xu Sun Zhiyuan Zhang Xuancheng Ren Ruixuan Luo Liangyou Li 30 39 0 10 Jun 2020
Universal Robust Regression via Maximum Mean Discrepancy Pierre Alquier Mathieu Gerber 38 15 0 01 Jun 2020
Generative Adversarial Networks (GANs Survey): Challenges, Solutions, and Future Directions Divya Saxena Jiannong Cao AAML AI4CE 26 287 0 30 Apr 2020
Adaptive Object Detection with Dual Multi-Label Prediction Z. Zhao Yuhong Guo Haifeng Shen Jieping Ye 27 54 0 29 Mar 2020
OpenGAN: Open Set Generative Adversarial Networks Luke Ditria Benjamin J. Meyer Tom Drummond VLM AI4CE GAN 43 20 0 18 Mar 2020
Multivariate time-series modeling with generative neural networks Marius Hofert Avinash Prasad Mu Zhu 24 6 0 25 Feb 2020
xAI-GAN: Enhancing Generative Adversarial Networks via Explainable AI Systems Vineel Nagisetty Laura Graves Joseph Scott Vijay Ganesh GAN DRL 26 27 0 24 Feb 2020
A Review on Generative Adversarial Networks: Algorithms, Theory, and Applications Jie Gui Zhenan Sun Yonggang Wen Dacheng Tao Jieping Ye EGVM 33 821 0 20 Jan 2020
Multi-Source Domain Adaptation for Text Classification via DistanceNet-Bandits Han Guo Ramakanth Pasunuru Joey Tianyi Zhou 30 114 0 13 Jan 2020
Triple Generative Adversarial Networks Chongxuan Li Kun Xu Jiashuo Liu Jun Zhu Bo Zhang GAN 33 41 0 20 Dec 2019
How to GAN away Detector Effects Marco Bellagente A. Butter Gregor Kasieczka Tilman Plehn R. Winterhalder GAN 21 86 0 01 Dec 2019
Prescribed Generative Adversarial Networks Adji Bousso Dieng Francisco J. R. Ruiz David M. Blei Michalis K. Titsias GAN DRL 27 61 0 09 Oct 2019
Conditional out-of-sample generation for unpaired data using trVAE M. Lotfollahi Mohsen Naghipourfar Fabian J. Theis F. A. Wolf GAN ViT DRL 24 19 0 04 Oct 2019
MMD-Bayes: Robust Bayesian Estimation via Maximum Mean Discrepancy Badr-Eddine Chérief-Abdellatif Pierre Alquier 56 72 0 29 Sep 2019
Minimum Stein Discrepancy Estimators Alessandro Barp François‐Xavier Briol Andrew B. Duncan Mark Girolami Lester W. Mackey 33 90 0 19 Jun 2019
Statistical Inference for Generative Models with Maximum Mean Discrepancy François‐Xavier Briol Alessandro Barp Andrew B. Duncan Mark Girolami 27 70 0 13 Jun 2019
Maximum Mean Discrepancy Gradient Flow Michael Arbel Anna Korba Adil Salim Arthur Gretton 27 159 0 11 Jun 2019
Generative Adversarial Networks in Computer Vision: A Survey and Taxonomy Zhengwei Wang Qi She T. Ward MedIm EGVM 29 90 0 04 Jun 2019
Kernel Conditional Density Operators Ingmar Schuster Mattes Mollenhauer Stefan Klus Krikamol Muandet 30 25 0 27 May 2019
Deep Signature Transforms Patrick Kidger Patrick Kidger Imanol Perez Arribas C. Salvi Terry Lyons SLR 27 126 0 21 May 2019
Meta-Sim: Learning to Generate Synthetic Datasets Amlan Kar Aayush Prakash Ming Liu Eric Cameracci Justin Yuan Matt Rusiniak David Acuna Antonio Torralba Sanja Fidler 22 248 0 25 Apr 2019
Learning Implicit Generative Models by Matching Perceptual Features Cicero Nogueira dos Santos Youssef Mroueh Inkit Padhi Pierre Dognin GAN 43 28 0 04 Apr 2019
Nonparametric Density Estimation & Convergence Rates for GANs under Besov IPM Losses Ananya Uppal Shashank Singh Barnabás Póczós 30 52 0 09 Feb 2019
Deep Generative Learning via Variational Gradient Flow Yuan Gao Yuling Jiao Yang Wang Yao Wang Can Yang Shunkang Zhang 27 36 0 24 Jan 2019
Kernel Change-point Detection with Auxiliary Deep Generative Models Wei-Cheng Chang Chun-Liang Li Yiming Yang Barnabás Póczós 16 67 0 18 Jan 2019
MAE: Mutual Posterior-Divergence Regularization for Variational AutoEncoders Xuezhe Ma Chunting Zhou Eduard H. Hovy DRL 28 39 0 06 Jan 2019
Improving MMD-GAN Training with Repulsive Loss Function Wei Wang Yuan Sun Saman K. Halgamuge GAN 17 79 0 24 Dec 2018
Conditional Recurrent Flow: Conditional Generation of Longitudinal Samples with Applications to Neuroimaging Seong Jae Hwang Zirui Tao Won Hwa Kim Vikas Singh MedIm 19 12 0 24 Nov 2018
Deep Knockoffs Yaniv Romano Matteo Sesia Emmanuel J. Candès BDL 18 139 0 16 Nov 2018
Learning Temporal Point Processes via Reinforcement Learning Shuang Li Shuai Xiao Shixiang Zhu Nan Du Yao Xie Le Song AI4TS 16 105 0 12 Nov 2018
Quasi-random sampling for multivariate distributions via generative neural networks Marius Hofert Avinash Prasad Mu Zhu 22 14 0 01 Nov 2018
Interpolating between Optimal Transport and MMD using Sinkhorn Divergences Jean Feydy Thibault Séjourné François-Xavier Vialard S. Amari A. Trouvé Gabriel Peyré OT 23 520 0 18 Oct 2018
Adversarial Balancing for Causal Inference Michal Ozery-Flato Pierre Thodoroff Matan Ninio Michal Rosen-Zvi T. El-Hay CML GAN 16 25 0 17 Oct 2018
A Kernel Perspective for Regularizing Deep Neural Networks A. Bietti Grégoire Mialon Dexiong Chen Julien Mairal 16 15 0 30 Sep 2018
Learning disentangled representation from 12-lead electrograms: application in localizing the origin of Ventricular Tachycardia P. Gyawali B. Horácek J. Sapp Linwei Wang 38 3 0 04 Aug 2018
Counterfactual Mean Embeddings Krikamol Muandet Motonobu Kanagawa Sorawit Saengkyongam S. Marukatat CML OffRL 26 39 0 22 May 2018
Nonparametric Density Estimation under Adversarial Losses Shashank Singh Ananya Uppal Boyue Li Chun-Liang Li Manzil Zaheer Barnabás Póczós GAN 29 56 0 22 May 2018
MONK -- Outlier-Robust Mean Embedding Estimation by Median-of-Means M. Lerasle Z. Szabó Gaspar Massiot Guillaume Lecué 36 35 0 13 Feb 2018
First Order Generative Adversarial Networks Calvin Seward Thomas Unterthiner Urs M. Bergmann Nikolay Jetchev Sepp Hochreiter GAN 40 8 0 13 Feb 2018
Demystifying MMD GANs Mikolaj Binkowski Danica J. Sutherland Michael Arbel Arthur Gretton EGVM 43 1,454 0 04 Jan 2018
How Well Can Generative Adversarial Networks Learn Densities: A Nonparametric View Tengyuan Liang GAN 27 37 0 21 Dec 2017
Geometrical Insights for Implicit Generative Modeling Léon Bottou Martín Arjovsky David Lopez-Paz Maxime Oquab 32 49 0 21 Dec 2017
Understanding GANs: the LQG Setting S. Feizi Changho Suh F. Xia David Tse 42 63 0 30 Oct 2017