4 papers
Uncovering the Generative Landscape of Diffusion Models: A Spectral-Guided Quality-Diversity Diffusion Framework
Hannah Janmohamed, Joao Correia, Penousal Machado +1
Denoising Diffusion Probabilistic Models have emerged as powerful generative priors across domains ranging from molecular design to high-resolution image synthesis. However, standa…
Evolutionary Token-Level Prompt Optimization for Diffusion Models
Domício 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…
Inference-Time Optimization of Prompt Embeddings in Diffusion Models: A Comparison of sep-CMA-ES and Adam
Domício 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…
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…