NILM as a regression versus classification problem: the importance of thresholding. - Daniel Precioso; David Gómez-Ullate (CoRR, 2020)

Tuna-AI: tuna biomass estimation with Machine Learning models trained on oceanography and echosounder FAD data. - Daniel Precioso; Manuel Navarro-García; Kathryn Gavira-O'Neill; Alberto Torres-Barrán; David Gordo; Victor Gallego-Alcalá; David Gómez-Ullate (CoRR, 2021)

How do tuna schools associate to dFADs? A study using echo-sounder buoys to identify global patterns. - Manuel Navarro-García; Daniel Precioso; Kathryn Gavira-O'Neill; Alberto Torres-Barrán; David Gordo; Víctor Gallego; David Gómez-Ullate (CoRR, 2022)

NeoCam: An Edge-Cloud Platform for Non-Invasive Real-Time Monitoring in Neonatal Intensive Care Units. - Ángel Ruiz-Zafra; Daniel Precioso; Blas Salvador; Simón Pedro Lubián-López; Javier Jiménez; Isabel Benavente-Fernández; Janet Pigueiras; David Gómez-Ullate; Lionel C. Gontard (IEEE J. Biomed. Health Informatics, 2023)

Thresholding methods in non-intrusive load monitoring. - Daniel Precioso; David Gómez-Ullate (J. Supercomput., 2023)

Hybrid search method for Zermelo's navigation problem. - Daniel Precioso; Robert Milson; Louis Bu; Yvonne Menchions; David Gómez-Ullate (Comput. Appl. Math., 2024)