Skip to search formSkip to main contentSkip to account menu

Generative adversarial networks

Generative adversarial networks are a neural network framework where a generative model is estimated via an adversarial process. Initially developed… 
Wikipedia (opens in a new tab)

Related topics

Related topics

2 relations

Broader (1)

Cognitive science
Generative model

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2020
2020
Rényi Generative Adversarial Networks
We propose a loss function for generative adversarial networks (GANs) using Renyi information measures with parameter $\alpha… 
Review
2019
Review
2019
Unsupervised Minimax: Adversarial Curiosity, Generative Adversarial Networks, and Predictability Minimization
I review unsupervised or self-supervised neural networks playing minimax games in game-theoretic settings. (i) Adversarial… 
2019
2019
Generative Adversarial Networks with Joint Distribution Moment Matching
Generative adversarial networks (GANs) have shown impressive power in the field of machine learning. Traditional GANs have… 
Review
2018
Review
2018
Generative adversarial networks and adversarial methods in biomedical image analysis
Generative adversarial networks (GANs) and other adversarial methods are based on a game-theoretical perspective on joint… 
2018
2018
Self-Supervised Generative Adversarial Networks
Conditional GANs are at the forefront of natural image synthesis. The main drawback of such models is the necessity for labelled… 
2018
2018
Generative Adversarial Network Architectures For Image Synthesis Using Capsule Networks
In this paper, we propose Generative Adversarial Network (GAN) architectures that use Capsule Networks for image-synthesis. Based… 
2018
2018
Semantic Image Synthesis via Conditional Cycle-Generative Adversarial Networks
Traditional approaches for semantic image synthesis mainly focus on text descriptions while ignoring the related structures and… 
2018
2018
Discrete Wasserstein Generative Adversarial Networks (DWGAN)
Generating complex discrete distributions remains as one of the challenging problems in machine learning. Existing techniques for… 
2017
2017
Object Discovery By Generative Adversarial & Ranking Networks
The deep generative adversarial networks (GAN) recently have been shown to be promising for different computer vision… 
2017
2017
Generative Adversarial Mapping Networks
Generative Adversarial Networks (GANs) have shown impressive performance in generating photo-realistic images. They fit… 
By clicking accept or continuing to use the site, you agree to the terms outlined in our Privacy Policy (opens in a new tab), Terms of Service (opens in a new tab), and Dataset License (opens in a new tab)