A Method for Building Prototypes in the Nearest Prototype Approach Based on Similarity Relations for Problems of Function Approximation. - Marilyn Bello-García; María Matilde García Lorenzo; Rafael Esteban Bello Pérez (MICAI (1), 2012)

Hacia la diversidad de la bandada: procedimiento RSVN usando una distribución de Lévy. - Gonzalo Nápoles Ruiz; Isel Grau García; Marilyn Bello-García; Rafael Bello Pérez (Computación y Sistemas, 2014)

Personnel Selection in a Competitive Environment. - Marilyn Bello-García; Rafael Bello 001; María Matilde García Lorenzo; Ann Nowé (Computación y Sistemas, 2016)

A Solution for the Team Selection Problem Using ACO. - Lázaro Lugo; Marilyn Bello; Ann Nowé; Rafael Bello 001 (ANTS Conference, 2018)

Expanding MLkNN Using Extended Rough Set Theory. - Gabriela Pérez; Marilyn Bello-García; Gonzalo Nápoles; María Matilde García Lorenzo; Rafael Bello 001; Koen Vanhoof (IWAIPR, 2018)

Reduction Methods for Multi-Label Datasets Based on Granular Computing. - Marilyn Bello; Gonzalo Nápoles; Koen Vanhoof; Rafael Bello 001 (BNAIC/BENELEARN, 2019)

Prototypes Generation from Multi-label Datasets Based on Granular Computing. - Marilyn Bello; Gonzalo Nápoles; Koen Vanhoof; Rafael Bello 001 (CIARP, 2019)

Methods to Edit Multi-label Training Sets Using Rough Sets Theory. - Marilyn Bello; Gonzalo Nápoles; Koen Vanhoof; Rafael Bello 001 (IJCRS, 2019)

Outliers Detection in Multi-label Datasets. - Marilyn Bello; Gonzalo Nápoles; Rafael Morera; Koen Vanhoof; Rafael Bello 001 (MICAI (1), 2020)

Feature and Label Association Based on Granulation Entropy for Deep Neural Networks. - Marilyn Bello; Gonzalo Nápoles; Ricardo Sánchez; Koen Vanhoof; Rafael Bello 001 (IJCRS, 2020)

Deep neural network to extract high-level features and labels in multi-label classification problems. - Marilyn Bello; Gonzalo Nápoles; Ricardo Sánchez; Rafael Bello 001; Koen Vanhoof (Neurocomputing, 2020)

Layer-Wise Relevance Propagation in Multi-label Neural Networks to Identify COVID-19 Associated Coinfections. - Marilyn Bello; Yaumara Aguilera; Gonzalo Nápoles; María M. García; Rafael Bello 001; Koen Vanhoof (IWAIPR, 2021)

Forward Composition Propagation for Explainable Neural Reasoning. - Isel Grau; Gonzalo Nápoles; Marilyn Bello; Yamisleydi Salgueiro (CoRR, 2021)

Data quality measures based on granular computing for multi-label classification. - Marilyn Bello; Gonzalo Nápoles; Koen Vanhoof; Rafael Bello 001 (Inf. Sci., 2021)

Long-term Cognitive Network-based architecture for multi-label classification. - Gonzalo Nápoles; Marilyn Bello; Yamisleydi Salgueiro (Neural Networks, 2021)

Explanation of Multi-Label Neural Networks with Layer-Wise Relevance Propagation. - Marilyn Bello; Gonzalo Nápoles; Koen Vanhoof; María M. García; Rafael Bello 001 (IJCNN, 2022)

ExplainLFS: Explaining neural architectures for similarity learning from local perturbations in the latent feature space. - Marilyn Bello; Pablo Costa; Gonzalo Nápoles; Pablo Mesejo; Oscar Cordón (Inf. Fusion, 2024)

REPROT: Explaining the predictions of complex deep learning architectures for object detection through reducts of an image. - Marilyn Bello; Gonzalo Nápoles; Leonardo Concepción; Rafael Bello 001; Pablo Mesejo; Oscar Cordón (Inf. Sci., 2024)

Forward Composition Propagation for Explainable Neural Reasoning. - Isel Grau; Gonzalo Nápoles; Marilyn Bello; Yamisleydi Salgueiro; Agnieszka Jastrzebska (IEEE Comput. Intell. Mag., 2024)

The level of strength of an explanation: A quantitative evaluation technique for post-hoc XAI methods. - Marilyn Bello; Rosalís Amador; María-Matilde García; Javier Del Ser; Pablo Mesejo; Oscar Cordón (Pattern Recognit., 2025)

Explainability in Context: A Multilevel Framework Aligning AI Explanations with Stakeholder with LLMs. - Marilyn Bello; Rafael Bello 001; María-Matilde García; Ann Nowé; Iván Sevillano-García; Francisco Herrera (CoRR, 2025)