The Numerics of GANs

30 May 2017

Papers citing "The Numerics of GANs"

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Title
Negative Stepsizes Make Gradient-Descent-Ascent Converge Henry Shugart Jason M. Altschuler 30 0 0 02 May 2025
BlockEcho: Retaining Long-Range Dependencies for Imputing Block-Wise Missing Data Qiao Han Mingqian Li Yao Yang Yiteng Zhai 41 0 0 29 Feb 2024
Aligning Individual and Collective Objectives in Multi-Agent Cooperation Yang Li Wenhao Zhang Jianhong Wang Shao Zhang Yali Du Ying Wen Wei Pan 26 1 0 19 Feb 2024
Optimal Guarantees for Algorithmic Reproducibility and Gradient Complexity in Convex Optimization Liang Zhang Junchi Yang Amin Karbasi Niao He 31 2 0 26 Oct 2023
Implicit Variational Inference for High-Dimensional Posteriors Anshuk Uppal Kristoffer Stensbo-Smidt Wouter Boomsma J. Frellsen BDL 26 1 0 10 Oct 2023
On a continuous time model of gradient descent dynamics and instability in deep learning Mihaela Rosca Yan Wu Chongli Qin Benoit Dherin 18 6 0 03 Feb 2023
Mind the (optimality) Gap: A Gap-Aware Learning Rate Scheduler for Adversarial Nets Hussein Hazimeh Natalia Ponomareva GAN 33 2 0 31 Jan 2023
Effects of Spectral Normalization in Multi-agent Reinforcement Learning K. Mehta Anuj Mahajan Kiran Ravish 24 7 0 10 Dec 2022
Generative Data Augmentation for Non-IID Problem in Decentralized Clinical Machine Learning Zirui Wang Shaoming Duan Chengyue Wu Wenhao Lin Xin-Xiang Zha Peiyi Han Chuanyi Liu MedIm 19 4 0 02 Dec 2022
Finding mixed-strategy equilibria of continuous-action games without gradients using randomized policy networks Carlos Martin T. Sandholm 28 11 0 29 Nov 2022
Max-Min Off-Policy Actor-Critic Method Focusing on Worst-Case Robustness to Model Misspecification Takumi Tanabe Reimi Sato Kazuto Fukuchi Jun Sakuma Youhei Akimoto OffRL 27 8 0 07 Nov 2022
Towards Multi-Agent Reinforcement Learning driven Over-The-Counter Market Simulations N. Vadori Leo Ardon Sumitra Ganesh Thomas Spooner Selim Amrouni Jared Vann Mengda Xu Zeyu Zheng T. Balch Manuela Veloso 18 16 0 13 Oct 2022
Why neural networks find simple solutions: the many regularizers of geometric complexity Benoit Dherin Michael Munn M. Rosca David Barrett 55 31 0 27 Sep 2022
HessianFR: An Efficient Hessian-based Follow-the-Ridge Algorithm for Minimax Optimization Yihang Gao Huafeng Liu Michael K. Ng Mingjie Zhou 25 2 0 23 May 2022
Riemannian Hamiltonian methods for min-max optimization on manifolds Andi Han Bamdev Mishra Pratik Jawanpuria Pawan Kumar Junbin Gao 35 17 0 25 Apr 2022
Signature and Log-signature for the Study of Empirical Distributions Generated with GANs J. Curtò I. D. Zarzà Hong-Mei Yan Carlos T. Calafate 23 1 0 07 Mar 2022
Convergence Rates of Two-Time-Scale Gradient Descent-Ascent Dynamics for Solving Nonconvex Min-Max Problems Thinh T. Doan 20 15 0 17 Dec 2021
Faster Single-loop Algorithms for Minimax Optimization without Strong Concavity Junchi Yang Antonio Orvieto Aurelien Lucchi Niao He 27 62 0 10 Dec 2021
The Geometric Occam's Razor Implicit in Deep Learning Benoit Dherin Micheal Munn David Barrett 22 6 0 30 Nov 2021
Generative Adversarial Networks and Adversarial Autoencoders: Tutorial and Survey Benyamin Ghojogh A. Ghodsi Fakhri Karray Mark Crowley GAN 34 12 0 26 Nov 2021
SyMetric: Measuring the Quality of Learnt Hamiltonian Dynamics Inferred from Vision I. Higgins Peter Wirnsberger Andrew Jaegle Aleksandar Botev 44 8 0 10 Nov 2021
Training Generative Adversarial Networks with Adaptive Composite Gradient Huiqing Qi Fang Li Shengli Tan Xiangyun Zhang GAN 26 3 0 10 Nov 2021
Which priors matter? Benchmarking models for learning latent dynamics Aleksandar Botev Andrew Jaegle Peter Wirnsberger Daniel Hennes I. Higgins AI4CE 35 28 0 09 Nov 2021
Don't Generate Me: Training Differentially Private Generative Models with Sinkhorn Divergence Tianshi Cao Alex Bie Arash Vahdat Sanja Fidler Karsten Kreis SyDa DiffM 19 71 0 01 Nov 2021
GDA-AM: On the effectiveness of solving minimax optimization via Anderson Acceleration Huan He Shifan Zhao Yuanzhe Xi Joyce C. Ho Y. Saad 34 1 0 06 Oct 2021
Adversarial Representation Learning With Closed-Form Solvers Bashir Sadeghi Lan Wang Vishnu Naresh Boddeti 37 5 0 12 Sep 2021
A Neural Tangent Kernel Perspective of GANs Jean-Yves Franceschi Emmanuel de Bézenac Ibrahim Ayed Mickaël Chen Sylvain Lamprier Patrick Gallinari 34 26 0 10 Jun 2021
Understanding Overparameterization in Generative Adversarial Networks Yogesh Balaji M. Sajedi Neha Kalibhat Mucong Ding Dominik Stöger Mahdi Soltanolkotabi S. Feizi AI4CE 22 21 0 12 Apr 2021
Regularizing Generative Adversarial Networks under Limited Data Hung-Yu Tseng Lu Jiang Ce Liu Ming-Hsuan Yang Weilong Yang GAN 35 142 0 07 Apr 2021
Deepfake Forensics via An Adversarial Game Zhi Wang Yiwen Guo W. Zuo AAML 21 34 0 25 Mar 2021
A Robust Adversarial Network-Based End-to-End Communications System With Strong Generalization Ability Against Adversarial Attacks Yudi Dong Huaxia Wang Yu-dong Yao AAML GAN 21 5 0 03 Mar 2021
DO-GAN: A Double Oracle Framework for Generative Adversarial Networks Aye Phyu Phyu Aung Xinrun Wang Runsheng Yu Bo An Senthilnath Jayavelu Xiaoli Li 29 8 0 17 Feb 2021
Combating Mode Collapse in GAN training: An Empirical Analysis using Hessian Eigenvalues Ricard Durall Avraam Chatzimichailidis P. Labus J. Keuper GAN 30 57 0 17 Dec 2020
Towards Generalized Implementation of Wasserstein Distance in GANs Minkai Xu Zhiming Zhou Guansong Lu Jian Tang Weinan Zhang Yong Yu 21 1 0 07 Dec 2020
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
Training Generative Adversarial Networks by Solving Ordinary Differential Equations Chongli Qin Yan Wu Jost Tobias Springenberg Andrew Brock Jeff Donahue Timothy Lillicrap Pushmeet Kohli GAN 26 28 0 28 Oct 2020
A Differential Game Theoretic Neural Optimizer for Training Residual Networks Guan-Horng Liu T. Chen Evangelos A. Theodorou 24 2 0 17 Jul 2020
Stochastic Hamiltonian Gradient Methods for Smooth Games Nicolas Loizou Hugo Berard Alexia Jolicoeur-Martineau Pascal Vincent Simon Lacoste-Julien Ioannis Mitliagkas 39 50 0 08 Jul 2020
A Convergent and Dimension-Independent Min-Max Optimization Algorithm Vijay Keswani Oren Mangoubi Sushant Sachdeva Nisheeth K. Vishnoi 15 1 0 22 Jun 2020
The limits of min-max optimization algorithms: convergence to spurious non-critical sets Ya-Ping Hsieh P. Mertikopoulos V. Cevher 32 81 0 16 Jun 2020
FedGAN: Federated Generative Adversarial Networks for Distributed Data M. Rasouli Tao Sun Ram Rajagopal FedML 30 143 0 12 Jun 2020
On the Impossibility of Global Convergence in Multi-Loss Optimization Alistair Letcher 24 32 0 26 May 2020
Regularization Methods for Generative Adversarial Networks: An Overview of Recent Studies Minhyeok Lee Junhee Seok GAN 27 25 0 19 May 2020
GANs May Have No Nash Equilibria Farzan Farnia Asuman Ozdaglar GAN 28 43 0 21 Feb 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
Accelerating Smooth Games by Manipulating Spectral Shapes Waïss Azizian Damien Scieur Ioannis Mitliagkas Simon Lacoste-Julien Gauthier Gidel 33 48 0 02 Jan 2020
Model Inversion Networks for Model-Based Optimization Aviral Kumar Sergey Levine OffRL 24 93 0 31 Dec 2019
Towards Better Understanding of Adaptive Gradient Algorithms in Generative Adversarial Nets Mingrui Liu Youssef Mroueh Jerret Ross Wei Zhang Xiaodong Cui Payel Das Tianbao Yang ODL 38 63 0 26 Dec 2019
Multi-Agent Reinforcement Learning: A Selective Overview of Theories and Algorithms Kaipeng Zhang Zhuoran Yang Tamer Basar 55 1,181 0 24 Nov 2019
Image Difficulty Curriculum for Generative Adversarial Networks (CuGAN) Petru Soviany Claudiu Ardei Radu Tudor Ionescu Marius Leordeanu GAN 19 47 0 20 Oct 2019