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ORCIDMarilyn Bello-García
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2020 – today
- 2024
[j8]Isel Grau
, Gonzalo Nápoles, Marilyn Bello, Yamisleydi Salgueiro, Agnieszka Jastrzebska:
Forward Composition Propagation for Explainable Neural Reasoning. IEEE Comput. Intell. Mag. 19(1): 26-35 (2024)- [j7]Marilyn Bello, Pablo Costa, Gonzalo Nápoles, Pablo Mesejo, Oscar Cordón:
ExplainLFS: Explaining neural architectures for similarity learning from local perturbations in the latent feature space. Inf. Fusion 108: 102407 (2024) - [j6]Marilyn Bello, Gonzalo Nápoles, Leonardo Concepción, Rafael Bello, Pablo Mesejo, Oscar Cordón:
REPROT: Explaining the predictions of complex deep learning architectures for object detection through reducts of an image. Inf. Sci. 654: 119851 (2024) - 2022
- [c10]Marilyn Bello, Gonzalo Nápoles, Koen Vanhoof, María M. García, Rafael Bello:
Explanation of Multi-Label Neural Networks with Layer-Wise Relevance Propagation. IJCNN 2022: 1-10 - 2021
- [j5]Marilyn Bello, Gonzalo Nápoles, Koen Vanhoof, Rafael Bello:
Data quality measures based on granular computing for multi-label classification. Inf. Sci. 560: 51-67 (2021) - [j4]Gonzalo Nápoles, Marilyn Bello, Yamisleydi Salgueiro:
Long-term Cognitive Network-based architecture for multi-label classification. Neural Networks 140: 39-48 (2021) - [c9]Marilyn Bello, Yaumara Aguilera, Gonzalo Nápoles, María M. García, Rafael Bello, Koen Vanhoof:
Layer-Wise Relevance Propagation in Multi-label Neural Networks to Identify COVID-19 Associated Coinfections. IWAIPR 2021: 3-12 - [i1]Isel Grau, Gonzalo Nápoles, Marilyn Bello, Yamisleydi Salgueiro:
Forward Composition Propagation for Explainable Neural Reasoning. CoRR abs/2112.12717 (2021) - 2020
- [j3]Marilyn Bello, Gonzalo Nápoles, Ricardo Sánchez, Rafael Bello, Koen Vanhoof:
Deep neural network to extract high-level features and labels in multi-label classification problems. Neurocomputing 413: 259-270 (2020) - [c8]Marilyn Bello, Gonzalo Nápoles, Rafael Morera, Koen Vanhoof, Rafael Bello:
Outliers Detection in Multi-label Datasets. MICAI (1) 2020: 65-75 - [c7]Marilyn Bello, Gonzalo Nápoles, Ricardo Sánchez, Koen Vanhoof, Rafael Bello:
Feature and Label Association Based on Granulation Entropy for Deep Neural Networks. IJCRS 2020: 225-235
2010 – 2019
- 2019
- [c6]Marilyn Bello, Gonzalo Nápoles, Koen Vanhoof, Rafael Bello:
Reduction Methods for Multi-Label Datasets Based on Granular Computing. BNAIC/BENELEARN 2019 - [c5]Marilyn Bello, Gonzalo Nápoles, Koen Vanhoof, Rafael Bello:
Prototypes Generation from Multi-label Datasets Based on Granular Computing. CIARP 2019: 142-151 - [c4]Marilyn Bello, Gonzalo Nápoles, Koen Vanhoof, Rafael Bello:
Methods to Edit Multi-label Training Sets Using Rough Sets Theory. IJCRS 2019: 369-380 - 2018
- [c3]Lázaro Lugo, Marilyn Bello, Ann Nowé, Rafael Bello:
A Solution for the Team Selection Problem Using ACO. ANTS Conference 2018: 325-332 - [c2]Gabriela Pérez, Marilyn Bello-García, Gonzalo Nápoles, María Matilde García Lorenzo, Rafael Bello, Koen Vanhoof:
Expanding MLkNN Using Extended Rough Set Theory. IWAIPR 2018: 247-254 - 2016
- [j2]Marilyn Bello-García, Rafael Bello, María Matilde García Lorenzo, Ann Nowé:
Personnel Selection in a Competitive Environment. Computación y Sistemas 20(2) (2016) - 2014
- [j1]Gonzalo Nápoles Ruiz, Isel Grau García, Marilyn Bello-García, Rafael Bello Pérez:
Hacia la diversidad de la bandada: procedimiento RSVN usando una distribución de Lévy. Computación y Sistemas 18(1) (2014) - 2012
- [c1]Marilyn Bello-García, María Matilde García Lorenzo, Rafael Esteban Bello Pérez:
A Method for Building Prototypes in the Nearest Prototype Approach Based on Similarity Relations for Problems of Function Approximation. MICAI (1) 2012: 39-50
Coauthor Index
aka: Gonzalo Nápoles Ruiz
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