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Araya-Diaz, P., Ruz, G. A., & Palomino, H. M. (2013). Discovering Craniofacial Patterns Using Multivariate Cephalometric Data for Treatment Decision Making in Orthodontics. Int. J. Morphol., 31(3), 1109–1115.
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Canals, C., Goles, E., Mascareno, A., Rica, S., & Ruz, G. A. (2018). School Choice in a Market Environment: Individual versus Social Expectations. Complexity, 3793095, 11 pp.
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Cho, A. D., Carrasco, R. A., Ruz, G. A., & Ortiz, J. L. (2020). Slow Degradation Fault Detection in a Harsh Environment. IEEE Access, 8, 175904–175920.
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Di Genova, A., Ruz, G. A., Sagot, M. F., & Maass, A. (2018). Fast-SG: an alignment-free algorithm for hybrid assembly. GigaScience, 7(5), 15 pp.
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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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Goles, E., Lobos, F., Ruz, G. A., & Sene, S. (2020). Attractor landscapes in Boolean networks with firing memory: a theoretical study applied to genetic networks. Nat. Comput., 19(2), 295–319.
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Goles, E., Montalva, M., & Ruz, G. A. (2013). Deconstruction and Dynamical Robustness of Regulatory Networks: Application to the Yeast Cell Cycle Networks. Bull. Math. Biol., 75(6), 939–966.
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Henriquez, P. A., & Ruz, G. A. (2017). Extreme learning machine with a deterministic assignment of hidden weights in two parallel layers. Neurocomputing, 226, 109–116.
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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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Henriquez, P. A., & Ruz, G. A. (2018). Twitter Sentiment Classification Based on Deep Random Vector Functional Link. In 2018 International Joint Conference on Neural Networks (IJCNN).
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Henriquez, P. A., & Ruz, G. A. (2019). Noise reduction for near-infrared spectroscopy data using extreme learning machines. Eng. Appl. Artif. Intell., 79, 13–22.
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Mascareno, A., Cordero, R., Azocar, G., Billi, M., Henriquez, P. A., & Ruz, G. A. (2018). Controversies in social-ecological systems: lessons from a major red tide crisis on Chiloe Island, Chile. Ecol. Soc., 23(4), 25 pp.
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Mascareno, A., Goles, E., & Ruz, G. A. (2016). Crisis in complex social systems: A social theory view illustrated with the chilean case. Complexity, 21(S2), 13–23.
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Mascareno, A., Henriquez, P. A., Billi, M., & Ruz, G. A. (2020). A Twitter-Lived Red Tide Crisis on Chiloe Island, Chile: What Can Be Obtained for Social-Ecological Research through Social Media Analysis? Sustainability, 12(20), 38 pp.
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Osores, S. J. A., Ruz, G. A., Opitz, T., & Lardies, M. A. (2018). Discovering divergence in the thermal physiology of intertidal crabs along latitudinal gradients using an integrated approach with machine learning. J. Therm. Biol., 78, 140–150.
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Pham, D. T., & Ruz, G. A. (2009). Unsupervised training of Bayesian networks for data clustering. Proc. R. Soc. A-Math. Phys. Eng. Sci., 465(2109), 2927–2948.
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Rengifo, F., Ruz, G. A., & Mascareno, A. (2018). Managing the 1920s' Chilean educational crisis: A historical view combined with machine learning. PLoS One, 13(5), 23 pp.
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Rodriguez-Valdecantos, G., Manzano, M., Sanchez, R., Urbina, F., Hengst, M. B., Lardies, M. A., et al. (2017). Early successional patterns of bacterial communities in soil microcosms reveal changes in bacterial community composition and network architecture, depending on the successional condition. Appl. Soil Ecol., 120, 44–54.
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Ruz, G. A. (2016). Improving the performance of inductive learning classifiers through the presentation order of the training patterns. Expert Syst. Appl., 58, 1–9.
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Ruz, G. A., & Araya-Diaz, P. (2018). Predicting Facial Biotypes Using Continuous Bayesian Network Classifiers. Complexity, 4075656, 14 pp.
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