Graph Neural Network Potentials for Molecular Dynamics Simulations of Water Cluster Anions. - Alfonso Gijón; Miguel Molina-Solana; Juan Gómez-Romero (ICCS (4), 2023)

Prediction of wind turbines power with physics-informed neural networks and evidential uncertainty quantification. - Alfonso Gijón; Ainhoa Pujana-Goitia; Eugenio Perea; Miguel Molina-Solana; Juan Gómez-Romero (CoRR, 2023)

Explainable Hybrid Semi-parametric Model for Prediction of Power Generated by Wind Turbines. - Alfonso Gijón; Simone Eiraudo; Antonio Manjavacas; Lorenzo Bottaccioli; Andrea Lanzini; Miguel Molina-Solana; Juan Gómez-Romero (ICCS (5), 2024)

STIED: A deep learning model for the SpatioTemporal detection of focal Interictal Epileptiform Discharges with MEG. - Raquel Fernández-Martín; Alfonso Gijón; Odile Feys; Elodie Juvené; Alec Aeby; Charline Urbain; Xavier De Tiège; Vincent Wens (CoRR, 2024)

Graph-neural-network potential energy surface to speed up Monte Carlo simulations of water cluster anions. - Alfonso Gijón; Miguel Molina-Solana; Juan Gómez-Romero (J. Comput. Sci., 2024)

Integrating physics and data-driven approaches: An explainable and uncertainty-aware hybrid model for wind turbine power prediction. - Alfonso Gijón; Simone Eiraudo; Antonio Manjavacas; Daniele Salvatore Schiera; Miguel Molina-Solana; Juan Gómez-Romero (Comput. Phys. Commun., 2025)