Gravitational-wave parameter inference using Deep Learning. - João D. Álvares; José A. Font; Felipe F. Freitas; Osvaldo Gramaxo Freitas; António P. Morais; Solange Nunes; António Onofre; Alejandro Torres-Forné (CBMI, 2021)

Boosting the performance of SOTA convolution-based networks with dimensionality reduction: An application on hyperspectral images of wine grape berries. - Rui Silva; Osvaldo Gramaxo Freitas; Pedro Melo-Pinto (Intell. Syst. Appl., 2023)

NRSurNN3dq4: A Deep Learning Powered Numerical Relativity Surrogate for Binary Black Hole Waveforms. - Osvaldo Gramaxo Freitas; Anastasios Theodoropoulos; Nino Villanueva; Tiago S. Fernandes; Solange Nunes; José A. Font; António Onofre; Alejandro Torres-Forné; José D. Martín-Guerrero (CoRR, 2024)

Evaluating the generalization ability of deep learning models: An application on sugar content estimation from hyperspectral images of wine grape berries. - Rui Silva; Osvaldo Gramaxo Freitas; Pedro Melo-Pinto (Expert Syst. Appl., 2024)

Comparison of neural network architectures for feature extraction from binary black hole merger waveforms. - Osvaldo Gramaxo Freitas; Juan Calderón Bustillo; José A. Font; Solange Nunes; António Onofre; Alejandro Torres-Forné (Mach. Learn. Sci. Technol., 2024)