Sustainable Personalisation and Explainability in Dyadic Data Systems. - Jorge Paz-Ruza; Carlos Eiras-Franco; Bertha Guijarro-Berdiñas; Amparo Alonso-Betanzos (KES, 2022)

Positive-Unlabelled learning for identifying new candidate Dietary Restriction-related genes among ageing-related genes. - Jorge Paz-Ruza; Alex Alves Freitas; Amparo Alonso-Betanzos; Bertha Guijarro-Berdiñas (Comput. Biol. Medicine, 2024)

Positive-Unlabelled Learning for Improving Image-based Recommender System Explainability. - Álvaro Fernández-Campa-González; Jorge Paz-Ruza; Amparo Alonso-Betanzos; Bertha Guijarro-Berdiñas (CoRR, 2024)

Sustainable transparency on recommender systems: Bayesian ranking of images for explainability. - Jorge Paz-Ruza; Amparo Alonso-Betanzos; Bertha Guijarro-Berdiñas; Brais Cancela; Carlos Eiras-Franco (Inf. Fusion, 2024)

Sustainable Techniques to Improve Data Quality for Training Image-Based Explanatory Models for Recommender Systems. - Jorge Paz-Ruza; David Esteban Martínez; Amparo Alonso-Betanzos; Bertha Guijarro-Berdiñas (ICANN (3), 2025)

Predictively Combatting Toxicity in Health-related Online Discussions through Machine Learning. - Jorge Paz-Ruza; Amparo Alonso-Betanzos; Bertha Guijarro-Berdiñas; Carlos Eiras-Franco (IJCNN, 2025)

Beyond RMSE and MAE: Introducing EAUC to Unmask Hidden Bias and Unfairness in Dyadic Regression Models. - Jorge Paz-Ruza; Amparo Alonso-Betanzos; Bertha Guijarro-Berdiñas; Brais Cancela; Carlos Eiras-Franco (IEEE Trans. Neural Networks Learn. Syst., 2025)