Publications (41)
GreenMachine: Automatic Design of Zero-Cost Proxies for Energy-Efficient NAS
Gabriel Cortês, Nuno Lourenço, Penousal Machado
Artificial Intelligence (AI) has driven innovations and created new opportunities across various sectors. However, leveraging domain-specific knowledge often requires automated too…
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…
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…
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…
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,…
Evolutionary Machine Learning meets Self-Supervised Learning: a comprehensive survey
Adriano Vinhas, João Correia, Penousal Machado
The number of studies that combine Evolutionary Machine Learning and self-supervised learning has been growing steadily in recent years. Evolutionary Machine Learning has been show…
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…
Evolutionary Token-Level Prompt Optimization for Diffusion Models
DomÃcio Pereira Neto, João Correia, Penousal Machado
Text-to-image diffusion models exhibit strong generative performance but remain highly sensitive to prompt formulation, often requiring extensive manual trial and error to obtain s…
Using Computer Vision Techniques for Moving Poster Design
Sérgio Rebelo, Pedro Martins, João Bicker +1
Graphic Design encompasses a wide range of activities from the design of traditional print media (e.g., books and posters) to site-specific (e.g., signage systems) and electronic m…
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…
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…
TensorGP -- Genetic Programming Engine in TensorFlow
Francisco Baeta, João Correia, Tiago Martins +1
In this paper, we resort to the TensorFlow framework to investigate the benefits of applying data vectorization and fitness caching methods to domain evaluation in Genetic Programm…
Using Computational Approaches in Visual Identity Design: A Visual Identity for the Design and Multimedia Courses of Faculty of Sciences and Technology of University of Coimbra
Sérgio M. Rebelo, Tiago Martins, Artur Rebelo +2
Computational approaches are beginning to be used to design dynamic visual identities fuelled by data and generative processes. In this work, we explore these computational approac…
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…
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…
Structured mutation inspired by evolutionary theory enriches population performance and diversity
Stefano Tiso, Pedro Carvalho, Nuno Lourenço +1
Grammar-Guided Genetic Programming (GGGP) employs a variety of insights from evolutionary theory to autonomously design solutions for a given task. Recent insights from evolutionar…
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…
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…
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…
Evotype: Towards the Evolution of Type Stencils
Tiago Martins, João Correia, Ernesto Costa +1
Typefaces are an essential resource employed by graphic designers. The increasing demand for innovative type design work increases the need for good technological means to assist t…
Adaptive Quantum Scaling Model for Histogram Distribution-based Quantum Watermarking
Zheng Xing, Chan-Tong Lam, Xiaochen Yuan +2
The development of quantum image representation and quantum measurement techniques has made quantum image processing research a hot topic. In this paper, a novel Adaptive Quantum S…
Speed Benchmarking of Genetic Programming Frameworks
Francisco Baeta, João Correia, Tiago Martins +1
Genetic Programming (GP) is known to suffer from the burden of being computationally expensive by design. While, over the years, many techniques have been developed to mitigate thi…
Boosting Mixed-Initiative Co-Creativity in Game Design: A Tutorial
Solange Margarido, LicÃnio Roque, Penousal Machado +1
In recent years, there has been a growing application of mixed-initiative co-creative approaches in the creation of video games. The rapid advances in the capabilities of artificia…
Evolutionary Optimization Trumps Adam Optimization on Embedding Space Exploration
DomÃcio Pereira Neto, João Correia, Penousal Machado
Deep diffusion models have revolutionized image generation by producing high-quality outputs. However, achieving specific objectives with these models often requires costly adaptat…
GreenFactory: Ensembling Zero-Cost Proxies to Estimate Performance of Neural Networks
Gabriel Cortês, Nuno Lourenço, Paolo Romano +1
Determining the performance of a Deep Neural Network during Neural Architecture Search processes is essential for identifying optimal architectures and hyperparameters. Traditional…
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…
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…
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,…
A Pig, an Angel and a Cactus Walk Into a Blender: A Descriptive Approach to Visual Blending
João M. Cunha, João Gonçalves, Pedro Martins +2
A descriptive approach for automatic generation of visual blends is presented. The implemented system, the Blender, is composed of two components: the Mapper and the Visual Blender…
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…
Generation of concept-representative symbols
João Miguel Cunha, Pedro Martins, AmÃlcar Cardoso +1
The visual representation of concepts or ideas through the use of simple shapes has always been explored in the history of Humanity, and it is believed to be the origin of writing.…
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…
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…
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…
Open Questions about Time and Self-reference in Living Systems
Samson Abramsky, Wolfgang Banzhaf, Leo S. D. Caves +5
Living systems exhibit a range of fundamental characteristics: they are active, self-referential, self-modifying systems. This paper explores how these characteristics create chall…
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…
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…
On the Dynamics of Mating Preferences in Genetic Programming
José Maria Simões, Nuno Lourenço, Penousal Machado
Several mating restriction techniques have been implemented in Evolutionary Algorithms to promote diversity. From similarity-based selection to niche preservation, the general goal…
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…
Probabilistic Structured Grammatical Evolution
Jessica Mégane, Nuno Lourenço, Penousal Machado
The grammars used in grammar-based Genetic Programming (GP) methods have a significant impact on the quality of the solutions generated since they define the search space by restri…
ESSYS* Sharing #UC: An Emotion-driven Audiovisual Installation
Sérgio M. Rebelo, Mariana Seiça, Pedro Martins +2
We present ESSYS* Sharing #UC, an audiovisual installation artwork that reflects upon the emotional context related to the university and the city of Coimbra, based on the data sha…