48 citations · 139 across the 9 of their papers we have counts for
16 papers
Co-evolutionary Probabilistic Structured Grammatical Evolution
Jessica Mégane, Nuno Lourenço, Penousal Machado
This work proposes an extension to Structured Grammatical Evolution (SGE) called Co-evolutionary Probabilistic Structured Grammatical Evolution (Co-PSGE). In Co-PSGE each individua…
On the Exploitation of Neuroevolutionary Information: Analyzing the Past for a More Efficient Future
Unai Garciarena, Nuno Lourenço, Penousal Machado +2
Neuroevolutionary algorithms, automatic searches of neural network structures by means of evolutionary techniques, are computationally costly procedures. In spite of this, due to t…
Evolving Learning Rate Optimizers for Deep Neural Networks
Pedro Carvalho, Nuno Lourenço, Penousal Machado
Artificial Neural Networks (ANNs) became popular due to their successful application difficult problems such image and speech recognition. However, when practitioners want to desig…
Probabilistic Grammatical Evolution
Jessica Mégane, Nuno Lourenço, Penousal Machado
Grammatical Evolution (GE) is one of the most popular Genetic Programming (GP) variants, and it has been used with success in several problem domains. Since the original proposal,…
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…
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…