Stabilizing Adversarial Training for Generative Networks-Reference-Cited by-同舟云学术

Stabilizing Adversarial Training for Generative Networks

Published:2023-12-15 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE International Conference on Big Data (BigData)
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Author:

Gerych Walter¹,Hickey Kevin¹,Hartvigsen Thomas²,Buquicchio Luke¹,Alajaji Abdulaziz³,Chandrasekaran Kavin⁴,Mansoor Hamid⁵,Agu Emmanuel¹,Rundensteiner Elke¹

Affiliation:

1. Worcester Polytechnic Institute,Department of Data Science,Worcester,MA

2. University of Virginia,School of Data Science,Charlottesville,VA

3. King Saud University,College of Computer and Informational Sciences,Riyadh,Saudi Arabia

4. Worcester Polytechnic Institute,Department of Computer Science,Worcester,MA

5. University of Victoria,Department of Computer Science,Victoria,BC,Canada

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10385234/10386078/10386654.pdf?arnumber=10386654

Reference50 articles.

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2. A State-of-the-Art Review on Image Synthesis With Generative Adversarial Networks

3. On convergence and stability of gans;Kodali;arXiv preprint arXiv:1705.07215,2017

4. Are gans created equal? a large-scale study;Lucic;Advances in neural information processing systems,2018

5. Towards principled methods for training generative adversarial networks;Arjovsky

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