activity
20222024
most citedContext Matters: Adaptive Mutation for Grammars

6 citations · 7 across the 6 of their papers we have counts for

collaborators

6 papers

cs.NE2024

Towards evolution of Deep Neural Networks through contrastive Self-Supervised learning

Adriano Vinhas, João Correia, Penousal Machado

Deep Neural Networks (DNNs) have been successfully applied to a wide range of problems. However, two main limitations are commonly pointed out. The first one is that they require l…

cs.MM2024

Evaluation Metrics for Automated Typographic Poster Generation

Sérgio M. Rebelo, J. J. Merelo, João Bicker +1

Computational Design approaches facilitate the generation of typographic design, but evaluating these designs remains a challenging task. In this paper, we propose a set of heurist…

cs.NE2024

Towards Physical Plausibility in Neuroevolution Systems

Gabriel Cortês, Nuno Lourenço, Penousal Machado

The increasing usage of Artificial Intelligence (AI) models, especially Deep Neural Networks (DNNs), is increasing the power consumption during training and inference, posing envir…

cs.NE2023

All You Need Is Sex for Diversity

José Maria Simões, Nuno Lourenço, Penousal Machado

Maintaining genetic diversity as a means to avoid premature convergence is critical in Genetic Programming. Several approaches have been proposed to achieve this, with some focusin…

cs.NE20236 cited

Context Matters: Adaptive Mutation for Grammars

Pedro Carvalho, Jessica Mégane, Nuno Lourenço +1

This work proposes Adaptive Facilitated Mutation, a self-adaptive mutation method for Structured Grammatical Evolution (SGE), biologically inspired by the theory of facilitated var…

cs.NE20221 cited

Exploring Generative Adversarial Networks for Text-to-Image Generation with Evolution Strategies

Victor Costa, Nuno Lourenço, João Correia +1

In the context of generative models, text-to-image generation achieved impressive results in recent years. Models using different approaches were proposed and trained in huge datas…