Machine learning in management of precautionary closures caused by lipophilic biotoxins. - Andres Molares-Ulloa; Enrique Fernández-Blanco; Alejandro Pazos; Daniel Rivero 001 (Comput. Electron. Agric., 2022)

Hybrid machine learning techniques in the management of harmful algal blooms impact. - Andres Molares-Ulloa; Daniel Rivero 001; Jesús Gil Ruiz; Enrique Fernández-Blanco; Luis de-la-Fuente-Valentín (Comput. Electron. Agric., 2023)

Harmful algal bloom forecasting. A comparison between stream and batch learning. - Andres Molares-Ulloa; Elisabet Rocruz; Daniel Rivero 001; Xosé A. Padin; Rita Nolasco; Jesús Dubert; Enrique Fernández-Blanco (CoRR, 2024)

Towards improved harmful algal bloom forecasts: A comparison of symbolic regression with DoME and stream learning performance. - Andres Molares-Ulloa; Elisabet Rocruz; Daniel Rivero 001; Xosé A. Padin; Rita Nolasco; Jesús Dubert; Enrique Fernández-Blanco (Comput. Electron. Agric., 2025)

Enhancing Orthopox Image Classification Using Hybrid Machine Learning and Deep Learning Models. - Alejandro Puente-Castro; Enrique Fernández-Blanco; Daniel Rivero 001; Andres Molares-Ulloa (CoRR, 2025)