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Generative adversarial networks

Generative adversarial networks are a neural network framework where a generative model is estimated via an adversarial process. Initially developed… 
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Papers overview

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2020
2020
We propose a loss function for generative adversarial networks (GANs) using Renyi information measures with parameter $\alpha… 
2019
2019
The conventional masked image restoration algorithms all utilise the correlation between the masked region and its neighbouring… 
Review
2019
Review
2019
GAN stands for Generative Adversarial Networks.GANs are the most interesting topics in Deep Learning. The concept of GAN is… 
Review
2018
Review
2018
Generative adversarial networks (GANs) and other adversarial methods are based on a game-theoretical perspective on joint… 
2018
2018
GANs excel at learning high dimensional distributions, but they can update generator parameters in directions that do not… 
2018
2018
This paper presents a deep neural architecture for synthesizing the frontal and neutral facial expression image of a subject… 
2018
2018
Conditional GANs are at the forefront of natural image synthesis. The main drawback of such models is the necessity for labelled… 
2018
2018
It is well-known that GANs are difficult to train, and several different techniques have been proposed in order to stabilize… 
2018
2018
In this paper, we propose Generative Adversarial Network (GAN) architectures that use Capsule Networks for image-synthesis. Based… 
2018
2018
Generative adversarial networks (GANs) have achieved outstanding success in generating the high quality data. Focusing on the…