105 citations · 282 across the 25 of their papers we have counts for
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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…
AutoLR: An Evolutionary Approach to Learning Rate Policies
Pedro Carvalho, Nuno Lourenço, Filipe Assunção +1
The choice of a proper learning rate is paramount for good Artificial Neural Network training and performance. In the past, one had to rely on experience and trial-and-error to fin…
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…
Evolution of Scikit-Learn Pipelines with Dynamic Structured Grammatical Evolution
Filipe Assunção, Nuno Lourenço, Bernardete Ribeiro +1
The deployment of Machine Learning (ML) models is a difficult and time-consuming job that comprises a series of sequential and correlated tasks that go from the data pre-processing…
Incremental Evolution and Development of Deep Artificial Neural Networks
Filipe Assunção, Nuno Lourenço, Bernardete Ribeiro +1
NeuroEvolution (NE) methods are known for applying Evolutionary Computation to the optimisation of Artificial Neural Networks(ANNs). Despite aiding non-expert users to design and t…