A Kernel-Based Approach to Estimating Phase Shifts Between Irregularly Sampled Time Series: An Application to Gravitational Lenses. - Juan Carlos Cuevas-Tello; Peter Tiño; Somak Raychaudhury (ECML, 2006)

How accurate are the time delay estimates in gravitational lensing? - Juan Carlos Cuevas-Tello; Peter Tiño; Somak Raychaudhury (CoRR, 2006)

Evolved Kernel Method for Time Series. - Juan Carlos Cuevas-Tello (MICAI, 2007)

Estimating time delays between irregularly sampled time series. - Juan Carlos Cuevas-Tello (2007)

Estimating Time Delay in Gravitationally Lensed Fluxes. - Peter Tiño; Juan Carlos Cuevas-Tello; Somak Raychaudhury (Similarity-based learning on structures, 2009)

IT Services for Decision Support Systems on Public Health Problems by using Genomic Data. - Juan Carlos Cuevas-Tello; Christian Alberto Garcia-Sepulveda; Héctor G. Pérez-González; Manuel Mora (BIOCOMP, 2010)

Uncovering delayed patterns in noisy and irregularly sampled time series: An astronomy application. - Juan Carlos Cuevas-Tello; Peter Tiño; Somak Raychaudhury; Xin Yao 001; Markus Harva (Pattern Recognit., 2010)

Software quality in terms of academic progress of developers. - Miriam Vázquez-Escalante; Jose Antonio Flores-Saucedo; Héctor G. Pérez-González; Juan Carlos Cuevas-Tello (SEKE, 2011)

Activity Inference for Ambient Intelligence Through Handling Artifacts in a Healthcare Environment. - Francisco Eduardo Martínez Pérez; José Ángel González-Fraga; Juan Carlos Cuevas-Tello; Marcela D. Rodríguez (Sensors, 2012)

Support vector machine algorithms in the search of KIR gene associations with disease. - Juan Carlos Cuevas-Tello; Daniel Hernández-Ramírez; Christian Alberto Garcia-Sepulveda (Comput. Biol. Medicine, 2013)

KIR Genes and Patterns Given by the A Priori Algorithm: Immunity for Haematological Malignancies. - J. Gilberto Rodríguez-Escobedo; Christian Alberto Garcia-Sepulveda; Juan Carlos Cuevas-Tello (Comput. Math. Methods Medicine, 2015)

A Tutorial on Deep Neural Networks for Intelligent Systems. - Juan Carlos Cuevas-Tello; Manuel Valenzuela-Rendón; Juan Arturo Nolazco-Flores (CoRR, 2016)

Apuntes de Redes Neuronales Artificiales. - Juan Carlos Cuevas-Tello (CoRR, 2018)

ModuleNet: A Convolutional Neural Network for Stereo Vision. - Octavio I. Renteria-Vidales; Juan Carlos Cuevas-Tello; Alan Reyes-Figueroa; Mariano Rivera (MCPR, 2020)

Fruit Classification for Retail Stores Using Deep Learning. - Jose Luis Rojas-Aranda; José Ignacio Nuñez-Varela; Juan Carlos Cuevas-Tello; Gabriela Rangel-Ramirez (MCPR, 2020)

Identification of HIV-1 Vif Protein Attributes Associated With CD4 T Cell Numbers and Viral Loads Using Artificial Intelligence Algorithms. - Jose S. Altamirano-Flores; Sandra E. Guerra-Palomares; Pedro G. Hernandez-Sanchez; Jose L. Ramirez-Garcialuna; J. Rafael Argüello-Astorga; Daniel E. Noyola; Juan Carlos Cuevas-Tello; Christian Alberto Garcia-Sepulveda (IEEE Access, 2020)

Ontology for knowledge condensation to support expertise location in the code phase during software development process. - Jose R. Martínez-García; Francisco Edgar Castillo-Barrera; Ramón R. Palacio; Gilberto Borrego; Juan Carlos Cuevas-Tello (IET Softw., 2020)

Fault Diagnosis Based on Machine Learning for the High Frequency Link of a Grid-Tied Photovoltaic Converter for a Wide Range of Irradiance Conditions. - Yuniel León-Ruiz; Mario González-García; Ricardo Alvarez-Salas; Juan Carlos Cuevas-Tello; Victor M. Cárdenas (IEEE Access, 2021)

Design of a Low-Power Embedded System Based on a SoC-FPGA and the Honeybee Search Algorithm for Real-Time Video Tracking. - Carlos Soubervielle-Montalvo; Oscar Ernesto Perez-Cham; Cesar Puente 001; Emilio J. González-Galván; Gustavo Olague; Carlos Arturo Aguirre-Salado; Juan Carlos Cuevas-Tello; Luis Javier Ontañón García (Sensors, 2022)

Knowledge Condensation Model to Support Expertise Location in Software Development. - Jose R. Martínez-García; Ramón René Palacio Cinco; Francisco Edgar Castillo-Barrera; Juan Carlos Cuevas-Tello; Gilberto Borrego (Computación y Sistemas (CyS), 2023)

Static Malware Analysis Using Low-Parameter Machine Learning Models. - Ryan Baker del Aguila; Carlos Daniel Contreras Pérez; Alejandra Guadalupe Silva Trujillo; Juan Carlos Cuevas-Tello; José I. Nuñez-Varela (Comput., 2024)