activity
20192021
most citedCOEGAN: Evaluating the Coevolution Effect in Generative Adversarial Networks

48 citations · 99 across the 3 of their papers we have counts for

collaborators

5 papers

cs.NE2021

Demonstrating the Evolution of GANs through t-SNE

Victor Costa, Nuno Lourenço, João Correia +1

Generative Adversarial Networks (GANs) are powerful generative models that achieved strong results, mainly in the image domain. However, the training of GANs is not trivial, presen…

cs.NE202019 cited

Exploring the Evolution of GANs through Quality Diversity

Victor Costa, Nuno Lourenço, João Correia +1

Generative adversarial networks (GANs) achieved relevant advances in the field of generative algorithms, presenting high-quality results mainly in the context of images. However, G…

cs.NE2020

Using Skill Rating as Fitness on the Evolution of GANs

Victor Costa, Nuno Lourenço, João Correia +1

Generative Adversarial Networks (GANs) are an adversarial model that achieved impressive results on generative tasks. In spite of the relevant results, GANs present some challenges…

cs.NE201948 cited

COEGAN: Evaluating the Coevolution Effect in Generative Adversarial Networks

Victor Costa, Nuno Lourenço, João Correia +1

Generative adversarial networks (GAN) present state-of-the-art results in the generation of samples following the distribution of the input dataset. However, GANs are difficult to…

cs.NE201932 cited

Coevolution of Generative Adversarial Networks

Victor Costa, Nuno Lourenço, Penousal Machado

Generative adversarial networks (GAN) became a hot topic, presenting impressive results in the field of computer vision. However, there are still open problems with the GAN model,…