Generative adversarial networks (GANs) have recently become a hot research topic;
however, they have been studied since 2014, and a large number of algorithms have been …

Generative Adversarial Networks (GANs) is a novel class of deep generative models that
has recently gained significant attention. GANs learn complex and high-dimensional …

We look into Generative Adversarial Network (GAN), its prevalent variants and applications
in a number of sectors. GANs combine two neural networks that compete against one …

Recently, the Generative Adversarial Networks (GANs) are fast becoming a key promising
research direction in computational intelligence. To improve the modeling ability of GANs …

Generative adversarial network (GANs) is one of the most important research avenues in the
field of artificial intelligence, and its outstanding data generation capacity has received wide …

Generative adversarial networks (GAN) has received great attention and made great
progress since its emergence in 2014. In this paper, we focus on the theoretical …

Generative Adversarial Networks (GANs) are a type of deep learning techniques that have
shown remarkable success in generating realistic images, videos, and other types of data …

Generative adversarial networks (GANs) have been extensively studied in the past few
years. Arguably their most significant impact has been in the area of computer vision where …

The Generative Models have gained considerable attention in unsupervised learning via a
new and practical framework called Generative Adversarial Networks (GAN) due to their …

Generative adversarial networks (GAN) are a powerful subclass of generative models.
Despite a very rich research activity leading to numerous interesting GAN algorithms, it is …