Marilyn Bello-García

According to our database, Marilyn Bello-García authored at least 20 papers between 2012 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

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

2024

Forward Composition Propagation for Explainable Neural Reasoning.

Isel Grau, Gonzalo Nápoles, Marilyn Bello, Yamisleydi Salgueiro, Agnieszka Jastrzebska

IEEE Comput. Intell. Mag., February, 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, Pablo Mesejo, Oscar Cordón

Inf. Sci., January, 2024

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

2022

Explanation of Multi-Label Neural Networks with Layer-Wise Relevance Propagation.

Marilyn Bello, Gonzalo Nápoles, Koen Vanhoof, María M. García, Rafael Bello

Proceedings of the International Joint Conference on Neural Networks, 2022

2021

Long-term Cognitive Network-based architecture for multi-label classification.

Gonzalo Nápoles, Marilyn Bello, Yamisleydi Salgueiro

Neural Networks, 2021

Data quality measures based on granular computing for multi-label classification.

Marilyn Bello, Gonzalo Nápoles, Koen Vanhoof, Rafael Bello

Inf. Sci., 2021

Forward Composition Propagation for Explainable Neural Reasoning.

Isel Grau, Gonzalo Nápoles, Marilyn Bello, Yamisleydi Salgueiro

CoRR, 2021

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, Koen Vanhoof

Proceedings of the Progress in Artificial Intelligence and Pattern Recognition, 2021

2020

Deep neural network to extract high-level features and labels in multi-label classification problems.

Marilyn Bello, Gonzalo Nápoles, Ricardo Sánchez, Rafael Bello, Koen Vanhoof

Neurocomputing, 2020

Feature and Label Association Based on Granulation Entropy for Deep Neural Networks.

Marilyn Bello, Gonzalo Nápoles, Ricardo Sánchez, Koen Vanhoof, Rafael Bello

Proceedings of the Rough Sets - International Joint Conference, 2020

Outliers Detection in Multi-label Datasets.

Marilyn Bello, Gonzalo Nápoles, Rafael Morera, Koen Vanhoof, Rafael Bello

Proceedings of the Advances in Soft Computing, 2020

2019

Methods to Edit Multi-label Training Sets Using Rough Sets Theory.

Marilyn Bello, Gonzalo Nápoles, Koen Vanhoof, Rafael Bello

Proceedings of the Rough Sets - International Joint Conference, 2019

Prototypes Generation from Multi-label Datasets Based on Granular Computing.

Marilyn Bello, Gonzalo Nápoles, Koen Vanhoof, Rafael Bello

Proceedings of the Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 2019

Reduction Methods for Multi-Label Datasets Based on Granular Computing.

Marilyn Bello, Gonzalo Nápoles, Koen Vanhoof, Rafael Bello

Proceedings of the 31st Benelux Conference on Artificial Intelligence (BNAIC 2019) and the 28th Belgian Dutch Conference on Machine Learning (Benelearn 2019), 2019

2018

Expanding MLkNN Using Extended Rough Set Theory.

Gabriela Pérez, Marilyn Bello-García, Gonzalo Nápoles, María Matilde García Lorenzo, Rafael Bello, Koen Vanhoof

Proceedings of the Progress in Artificial Intelligence and Pattern Recognition, 2018

A Solution for the Team Selection Problem Using ACO.

Lázaro Lugo, Marilyn Bello, Ann Nowé, Rafael Bello

Proceedings of the Swarm Intelligence - 11th International Conference, 2018

2016

Personnel Selection in a Competitive Environment.

Marilyn Bello-García, Rafael Bello, María Matilde García Lorenzo, Ann Nowé

Computación y Sistemas, 2016

2014

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

2012

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

Proceedings of the Advances in Artificial Intelligence, 2012