| Recognition of an obstacle in a flow using artificial neural networks M Carrillo, U Que, JA González, C López Physical Review E 96 (2), 023306, 2017 | 10 | 2017 |
| Estimation of Reynolds number for flows around cylinders with lattice Boltzmann methods and artificial neural networks M Carrillo, U Que, JA González Physical Review E 94 (6), 063304, 2016 | 6 | 2016 |
| Determination of thermodynamic state variables of liquids from their microscopic structures using an artificial neural network U Que-Salinas, PE Ramírez-González, A Torres-Carbajal Soft Matter 17 (7), 1975-1984, 2021 | 4 | 2021 |
| On the Prediction of In Vitro Arginine Glycation of Short Peptides Using Artificial Neural Networks U Que-Salinas, D Martinez-Peon, AD Reyes-Figueroa, I Ibarra, ... Sensors 22 (14), 5237, 2022 | 2 | 2022 |
| Estimation of the Reynolds number in a Poiseuille flow using artificial neural networks M Carrillo, JA Gónzalez, U Que Journal of Physics: Conference Series 792 (1), 012071, 2017 | 2 | 2017 |
| Prediction of equations of state of molecular liquids by an artificial neural network A Torres-Carbajal, U Que-Salinas, PE Ramírez-González Revista mexicana de física 68 (6), 0-0, 2022 | 1 | 2022 |
| Preparando un monitoreo más sistemático del volcán Pico de Orizaba usando herramientas modernas de redes neuronales e Inteligencia Artificial SUQ Salinas, K Sieron, FC Montiel, R Torres-Orozco, SFJ Cerrillo, ... UVserva, 54-64, 2022 | | 2022 |
| On the prediction of arginine glycation using artificial neural networks U Que-Salinas, D Martinez-Peon, AD Reyes-Figueroa, I Ibarra, ... bioRxiv, 2022.06. 05.494871, 2022 | | 2022 |
| Simulación numérica de flujos confinados mediante SPH y LBM SU Que Salinas Universidad Michoacana de San Nicolás de Hidalgo, 2018 | | 2018 |
| Optimización de datos iniciales para el método SPH SU Que Salinas Universidad Michoacana de San Nicolás de Hidalgo, 2014 | | 2014 |
