activity
20172023
most citedDENSER: Deep Evolutionary Network Structured Representation

105 citations · 165 across the 8 of their papers we have counts for

collaborators

9 papers

cs.AI2023★ 1 cited

Natural language to SQL in low-code platforms

Sofia Aparicio, Samuel Arcadinho, João Nadkarni +5

One of the developers' biggest challenges in low-code platforms is retrieving data from a database using SQL queries. Here, we propose a pipeline allowing developers to write natur…

cs.SE2023

CHAMELEON: OutSystems Live Bidirectional Transformations

Hugo Lourenço, João Costa Seco, Carla Ferreira +4

In model-driven engineering, the bidirectional transformation of models plays a crucial role in facilitating the use of editors that operate at different levels of abstraction. Thi…

cs.NE2020★ 7 cited

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…

cs.NE2020

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…

cs.NE2020

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…

cs.NE2019★ 26 cited

Automatic Design of Artificial Neural Networks for Gamma-Ray Detection

Filipe Assunção, João Correia, Rúben Conceição +4

The goal of this work is to investigate the possibility of improving current gamma/hadron discrimination based on their shower patterns recorded on the ground. To this end we propo…

cs.NE2019★ 6 cited

Fast-DENSER++: Evolving Fully-Trained Deep Artificial Neural Networks

Filipe Assunção, Nuno Lourenço, Penousal Machado +1

This paper proposes a new extension to Deep Evolutionary Network Structured Evolution (DENSER), called Fast-DENSER++ (F-DENSER++). The vast majority of NeuroEvolution methods that…

cs.NE2018★ 105 cited

DENSER: Deep Evolutionary Network Structured Representation

Filipe Assunção, Nuno Lourenço, Penousal Machado +1

Deep Evolutionary Network Structured Representation (DENSER) is a novel approach to automatically design Artificial Neural Networks (ANNs) using Evolutionary Computation. The algor…

cs.NE2017★ 20 cited

Towards the Evolution of Multi-Layered Neural Networks: A Dynamic Structured Grammatical Evolution Approach

Filipe Assunção, Nuno Lourenço, Penousal Machado +1

Current grammar-based NeuroEvolution approaches have several shortcomings. On the one hand, they do not allow the generation of Artificial Neural Networks (ANNs composed of more th…