Óscar Gabriel Reyes Pupo

Навело

	Све	Од 2020
Наводи	1171	918
h-индекс	18	15
i10-индекс	21	21

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Коаутори

Sebastián Ventura (ORCID: 0000-000...Professor of Computing and Artificial Intelligence, University of Cordoba (RoR:05yc77b46)Верификована је имејл адреса на uco.es
Justo P. CastañoIMIBIC, Universidad de CordobaВерификована је имејл адреса на uco.es
Carlos MorellProfessor of Computer Science, Universidad Central "Marta Abreu" de Las VillasВерификована је имејл адреса на uclv.edu.cu
Emilia Alors PérezMaimonides Institute of Biomedical Research of Cordoba (IMIBIC); Reina Sofia University Hospital (HURS); Department of Cell Biology, Physiology and Immunology, University of Cordoba (UCO); CIBER Physiopathology of Obesity and Nutrition (CIBERobn); Agrifood Campus of International Excellence (CeiA3), Cordoba, Spain.Верификована је имејл адреса на uco.es
Eduardo Pérez Perdomo (ORCID: 000...University of Cordoba, SpainВерификована је имејл адреса на uco.es
Habib M. FardounKing Abdulaziz UniversityВерификована је имејл адреса на kau.edu.sa
José Lopez-MirandaProfesor de Medicina. Hospital Universitario Reina Sofía. IMIBIC. Universidad de Córdoba. CIBEROBNВерификована је имејл адреса на uco.es
Jose M. MoyanoAssociate professor at Dpt. of Computer Science and Artificial Intelligence, University of SevillaВерификована је имејл адреса на us.es
María del Carmen Rodríguez-Hernánd...Ph.D., University of ZaragozaВерификована је имејл адреса на unizar.es
Alberto CanoAssociate Vice President for Research Computing, Virginia Tech, USAВерификована је имејл адреса на vt.edu
José María Luna (ORCID: 0000-0003-...Associate Professor of Computing and Artificial Intelligence, University of CordobaВерификована је имејл адреса на uco.es

Прати

Óscar Gabriel Reyes Pupo

Lead Data Scientist at Indivi (a dba of Healios AG)

Верификована је имејл адреса на indivi.io

Deep Learning Machine Learning Data mining Metaheuristics Algorithms and Data structures


Наслов Сортирај по наводима Сортирај по години Сортирај по наслову	Навело Навело	Година
Scalable extensions of the ReliefF algorithm for weighting and selecting features on the multi-label learning context O Reyes, C Morell, S Ventura Neurocomputing 161, 168-182, 2015	227	2015
Dysregulation of the splicing machinery is directly associated to aggressiveness of prostate cancer JM Jiménez-Vacas, V Herrero-Aguayo, AJ Montero-Hidalgo, ... EBioMedicine 51, 2020	96	2020
Effective active learning strategy for multi-label learning O Reyes, C Morell, S Ventura Neurocomputing 273, 494-508, 2018	84	2018
Splicing machinery dysregulation drives glioblastoma development/aggressiveness: oncogenic role of SRSF3 AC Fuentes-Fayos, MC Vázquez-Borrego, JM Jimenez-Vacas, L Bejarano, ... Brain 143 (11), 3273-3293, 2020	79	2020
Performing Multi-Target Regression via a Parameter Sharing-based Deep Network O Reyes, S Ventura International Journal of Neural Systems 29 (9 (1950014)), 1-22, 2019	74	2019
Dysregulation of the splicing machinery is associated to the development of non-alcoholic fatty liver disease M del Río-Moreno, E Alors-Pérez, S González-Rubio, G Ferrín, O Reyes, ... The Journal of Clinical Endocrinology & Metabolism, jc.2019-00021, https …, 2019	68	2019
Convolutional neural networks for the automatic diagnosis of melanoma: An extensive experimental study E Perez, O Reyes, S Ventura Medical image analysis 67, 101858, 2021	66	2021
Statistical comparisons of active learning strategies over multiple datasets O Reyes, AH Altalhi, S Ventura Knowledge-Based Systems 145, 274-288, 2018	64	2018
Evolutionary Strategy to perform Batch-Mode Active Learning on Multi-Label Data O Reyes, S Ventura ACM Transactions on Intelligent Systems and Technology 9 (4), 46:1--46:26, 2018	49	2018
Evolutionary feature weighting to improve the performance of multi-label lazy algorithms O Reyes, C Morell, S Ventura Integrated Computer-Aided Engineering 21 (4), 339-354, 2014	47	2014
Changes in splicing machinery components influence, precede, and early predict the development of type 2 diabetes: from the CORDIOPREV study MD Gahete, M del Rio-Moreno, A Camargo, JF Alcala-Diaz, E Alors-Perez, ... EBioMedicine 37, 356-365, 2018	38	2018
ReliefF-ML: an extension of ReliefF algorithm to multi-label learning OGR Pupo, C Morell, SV Soto Progress in Pattern Recognition, Image Analysis, Computer Vision, and …, 2013	38	2013
Effective lazy learning algorithm based on a data gravitation model for multi-label learning O Reyes, C Morell, S Ventura Information Sciences 340, 159-174, 2016	33	2016
Signal Speech Reconstruction and Noise removal using Convolutional Denoising Audioencoders with Neural Deep Learning A Houda, O Chakkor, O Reyes, S Ventura Analog Integrated Circuits and Signal Processing. https://doi.org/10.1007 …, 2019	32	2019
JCLAL: A Java Framework for Active Learning O Reyes, E Pérez, M del Carmen Rodrıguez-Hernández, HM Fardoun, ... Journal of Machine Learning Research 17 (95), 1-5, 2016	31	2016
A locally weighted learning method based on a data gravitation model for multi-target regression O Reyes, A Cano, HM Fardoun, S Ventura International Journal of Computational Intelligence Systems 11, 282-295, 2018	28	2018
Reliability and Acceptance of dreaMS, a Software Application for People with Multiple Sclerosis – a Feasibility Study T Woelfle, S Pless, Ó Reyes, A Wiencierz, A Feinstein, P Calabrese, ... Journal of Neurology, 2022	22	2022
Performing multi-target regression via gene expression programming-based ensemble models J Moyano, O Reyes, S Fardoun, Habib M., Ventura Neurocomputing 432 (7), 275-287, 2021	20	2021
Spliceosomic dysregulation unveils NOVA1 as a candidate actionable therapeutic target in pancreatic neuroendocrine tumors S Pedraza-Arevalo, E Alors-Pérez, R Blázquez-Encinas, ... Translational Research 251, 63-73, 2023	16	2023
An ensemble-based method for the selection of instances in the multi-target regression problem O Reyes, H Fardoun, S Ventura Integrated Computer-Aided Engineering 25 (4), 305-320, 2018	13	2018

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