Modelling Machine Learning Models. - Raül Fabra-Boluda; Cèsar Ferri; José Hernández-Orallo; Fernando Martínez-Plumed; M. José Ramírez-Quintana (PT-AI, 2017)

Identifying the Machine Learning Family from Black-Box Models. - Raül Fabra-Boluda; Cèsar Ferri; José Hernández-Orallo; Fernando Martínez-Plumed; María José Ramírez-Quintana (CAEPIA, 2018)

Family and Prejudice: A Behavioural Taxonomy of Machine Learning Techniques. - Raül Fabra-Boluda; Cèsar Ferri; Fernando Martínez-Plumed; José Hernández-Orallo; M. José Ramírez-Quintana (ECAI, 2020)

A Fine-Grained Study of Interpretability of Convolutional Neural Networks for Text Classification. - Maite Giménez; Ares Fabregat-Hernández; Raül Fabra-Boluda; Javier Palanca; Vicent J. Botti (HAIS, 2022)

Robustness Testing of Machine Learning Families using Instance-Level IRT-Difficulty. - Raül Fabra-Boluda; Cèsar Ferri; Fernando Martínez-Plumed; María José Ramírez-Quintana (EBeM@IJCAI, 2022)

Unveiling the robustness of machine learning families. - Raül Fabra-Boluda; Cèsar Ferri; María José Ramírez-Quintana; Fernando Martínez-Plumed (Mach. Learn. Sci. Technol., 2024)

Cracking black-box models: Revealing hidden machine learning techniques behind their predictions. - Raül Fabra-Boluda; Cèsar Ferri; José Hernández-Orallo; M. José Ramrez-Quintana; Fernando Martínez-Plumed (Intell. Data Anal., 2025)