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Allende, H., Salas, R., & Moraga, C. (2003). A robust and effective learning algorithm for feedforward neural networks based on the influence function. Lect. Notes Comput. Sc., 2652, 28–36.
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Cho, A. D., Carrasco, R. A., & Ruz, G. A. (2022). A RUL Estimation System from Clustered Run-to-Failure Degradation Signals. Sensors, 22(14), 5323.
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de la Cruz, R., Padilla, O., Valle, M. A., & Ruz, G. A. (2021). Modeling Recidivism through Bayesian Regression Models and Deep Neural Networks. Mathematics, 9(6), 639.
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Fernandez, C., Valle, C., Saravia, F., & Allende, H. (2012). Behavior analysis of neural network ensemble algorithm on a virtual machine cluster. Neural Comput. Appl., 21(3), 535–542.
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Goles, E., & Palacios, A. G. (2007). Dynamical complexity in cognitive neural networks. Biol. Res., 40(4), 479–485.
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Goles, E., & Ruz, G. A. (2015). Dynamics of neural networks over undirected graphs. Neural Netw., 63, 156–169.
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Henriquez, P. A., & Ruz, G. A. (2018). A non-iterative method for pruning hidden neurons in neural networks with random weights. Appl. Soft. Comput., 70, 1109–1121.
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Ruz, G. A., Zuniga, A., & Goles, E. (2018). A Boolean network model of bacterial quorum-sensing systems. Int. J. Data Min. Bioinform., 21(2), 123–144.
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Salas, R., Allende, H., Moreno, S., & Saavedra, C. (2005). Flexible Architecture of Self Organizing Maps for changing environments. Lect. Notes Comput. Sc., 3773, 642–653.
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