| Return random walks for link prediction M Curado Information Sciences 510, 99-107, 2020 | 27 | 2020 |
| A novel measure to identify influential nodes: return random walk gravity centrality M Curado, L Tortosa, JF Vicent Information Sciences 628, 177-195, 2023 | 23 | 2023 |
| Extending the adapted PageRank algorithm centrality to multiplex networks with data using the PageRank two-layer approach T Agryzkov, M Curado, F Pedroche, L Tortosa, JF Vicent Symmetry 11 (2), 284, 2019 | 22 | 2019 |
| Analysis and comparison of centrality measures applied to urban networks with data M Curado, L Tortosa, JF Vicent, G Yeghikyan Journal of Computational Science 43, 101127, 2020 | 20 | 2020 |
| Anew centrality measure in dense networks based on two-way random walk betweenness M Curado, R Rodriguez, L Tortosa, JF Vicent Applied Mathematics and Computation 412, 126560, 2022 | 18 | 2022 |
| The mutual information between graphs F Escolano, ER Hancock, MA Lozano, M Curado Pattern Recognition Letters 87, 12-19, 2017 | 16 | 2017 |
| A centrality model for directed graphs based on the Two-Way-Random Path and associated indices for characterizing the nodes M Curado, R Rodriguez, F Terroso-Saenz, L Tortosa, JF Vicent Journal of Computational Science 63, 101819, 2022 | 14 | 2022 |
| Dirichlet graph densifiers F Escolano, M Curado, MA Lozano, ER Hancook Structural, Syntactic, and Statistical Pattern Recognition: Joint IAPR …, 2016 | 14 | 2016 |
| On the interplay between strong regularity and graph densification M Fiorucci, A Torcinovich, M Curado, F Escolano, M Pelillo Graph-Based Representations in Pattern Recognition: 11th IAPR-TC-15 …, 2017 | 12 | 2017 |
| Early detection of Alzheimer’s disease: Detecting asymmetries with a return random walk link predictor M Curado, F Escolano, MA Lozano, ER Hancock Entropy 22 (4), 465, 2020 | 11 | 2020 |
| Understanding mobility in Rome by means of a multiplex network with data M Curado, L Tortosa, JF Vicent, G Yeghikyan Journal of Computational Science 51, 101305, 2021 | 10 | 2021 |
| Commute times in dense graphs F Escolano, M Curado, ER Hancock Structural, Syntactic, and Statistical Pattern Recognition: Joint IAPR …, 2016 | 10 | 2016 |
| Deep learning model of convolutional neural networks powered by a genetic algorithm for prevention of traffic accidents severity L Pérez-Sala, M Curado, L Tortosa, JF Vicent Chaos, Solitons & Fractals 169, 113245, 2023 | 9 | 2023 |
| An analysis of twitter as a relevant human mobility proxy: A comparative approach in spain during the COVID-19 pandemic F Terroso-Saenz, A Muñoz, F Arcas, M Curado GeoInformatica 26 (4), 677-706, 2022 | 9 | 2022 |
| Network embedding from the line graph: Random walkers and boosted classification MA Lozano, F Escolano, M Curado, ER Hancock Pattern Recognition Letters 143, 36-42, 2021 | 7 | 2021 |
| Mechanism Cleaning of the Ear Canal R Rodríguez, M Curado, R Pastor, J Toribio Inventions 7 (1), 20, 2022 | 5 | 2022 |
| Identifying mobility patterns by means of centrality algorithms in multiplex networks M Curado, L Tortosa, JF Vicent Applied Mathematics and Computation 406, 126269, 2021 | 5 | 2021 |
| Dirichlet densifiers for improved commute times estimation M Curado, F Escolano, MA Lozano, ER Hancock Pattern Recognition 91, 56-68, 2019 | 5 | 2019 |
| Net4lap: neural laplacian regularization for ranking and re-ranking M Curado, F Escolano, MA Lozano, ER Hancock 2018 24th International Conference on Pattern Recognition (ICPR), 1366-1371, 2018 | 4 | 2018 |
| Shape simplification through graph sparsification F Escolano, M Curado, S Biasotti, ER Hancock Graph-Based Representations in Pattern Recognition: 11th IAPR-TC-15 …, 2017 | 4 | 2017 |
Francisco Escolano RuizFull Profesor (University of Alicante)Verified email at dccia.ua.es
