Cho, A.D., Carrasco, R.A., Ruz, G.A. Improving Prescriptive Maintenance by Incorporating Post-Prognostic Information Through Chance Constraints, IEEE Access, Vol. 10, 2022, 55924-55932.
Billi, M., Mascareño, A., Henríquez, P.A., Rodríguez, I., Padilla, F., Ruz, G.A. Learning from crises? The long and winding road of the salmon industry in Chiloé Island, Chile, Marine Policy, Vol. 120, 2022, 105069.
Gregor, C., Ashlock, D., Ruz, G.A., MacKinnon, D., Kribs, D. A novel linear representation for evolving matrices, Soft Computing, Vol. 26, 2022, 6645-6657.
Cordero, R., Mascareño, A., Henríquez, P.A., Ruz, G.A. Drawing Constitutional Boundaries: A Digital Historical Analysis of the Writing Process of Pinochet’s 1980 Authoritarian Constitution, Historical Methods: A Journal of Quantitative and Interdisciplinary History, 2022, DOI: 10.1080/01615440.2022.2065396
Ruz, G.A., Henríquez, P.A., Mascareño, A. Bayesian Constitutionalization: Twitter Sentiment Analysis of the Chilean Constitutional Process through Bayesian Network Classifiers, Mathematics, Vol. 10, 2022, 166.
Truffello, R., Flores, M., Garretón, M., Ruz, G. La importancia del espacio geográfico para minimizar el error de muestras representativas, Revista de Geografía Norte Grande, Vol. 81, 2022, 137-160.
Andaur, J.M.R., Ruz, G.A., Goycoolea, M. Predicting Out-of-Stock Using Machine Learning: An Application in a Retail Packaged Foods Manufacturing Company, Electronics, Vol. 10, 2021, 2787.
de la Cruz, R., Padilla, O., Valle, M.A., Ruz, G.A. Modeling Recidivism through Bayesian Regression Models and Deep Neural Networks, Mathematics, Vol. 9, 2021, 639.
Montalva-Medel, M., Ledger, T., Ruz, G.A., Goles, E. Lac operon Boolean models: dynamical robustness and alternative improvements, Mathematics, Vol. 9, 2021, 600.
Valle, M.A., Ruz, G.A. Finding hierarchical structures of disordered systems: An application for market basket analysis, IEEE Access, Vol. 9, 2021, 1626-1641.
Mascareño, A., Henríquez, P.A., Billi, M., Ruz, G.A. A Twitter-Lived Red Tide Crisis on Chiloé Island, Chile: What Can Be Obtained for Social-Ecological Research through Social Media Analysis?, Sustainability, Vol. 12, 2020, 8506.
Cho, A.D., Carrasco, R.A., Ruz, G.A., Ortiz, J.L. Slow Degradation Fault Detection in a Harsh Environment, IEEE Access, Vol. 8, 2020, 175904-175920.
Goles, E., Lobos, F., Ruz, G.A., Sené, S. Attractor landscapes in Boolean networks with firing memory: a theoretical study applied to genetic networks, Natural Computing, 19, 2020, 295-319.
Timmermann, T., González, B., Ruz, G.A. Reconstruction of a gene regulatory network of the induced systemic resistance defense response in Arabidopsis using boolean networks, BMC Bioinformatics, 21, 142, 2020.
Ruz, G.A., Henríquez, P.A., Mascareño, A. Sentiment analysis of Twitter data during critical events through Bayesian networks classifiers, Future Generation Computer Systems, Vol. 106, 2020, 92-104.
Timmermann, T., Poupin, M.J., Vega, A., Urrutia, C., Ruz, G.A., González, B. Gene networks underlying the early regulation of Paraburkholderia phytofirmans PsJN induced systemic resistance in Arabidopsis, PLoS ONE, 14 (8), 2019, e0221358.
Valle, M.A., Ruz, G.A., Rica, S. Market basket analysis by solving the inverse Ising problem: Discovering pairwise interaction strengths among products, Physica A: Statistical Mechanics and its Applications, Vol. 524, 2019, 36-44.
Henríquez, P.A., Ruz, G.A. Noise reduction for near-infrared spectroscopy data using extreme learning machines, Engineering Applications of Artificial Intelligence, Vol. 79, 2019, 13-22.
Ruz, G.A., Araya-Díaz, P. Predicting facial biotypes using continuous Bayesian network classifiers, Complexity, Vol. 2018, Article ID 4075656, 14 pages, 2018.
Canals, C., Goles, E., Mascareño, A., Rica, S., Ruz, G.A. School choice in a market environment: individual vs. social expectations, Complexity, Vol. 2018, Article ID 3793095, 11 pages, 2018.
Ruz, G.A., Zúñiga, A., Goles, E. A Boolean network model of bacterial quorum-sensing systems, International Journal of Data Mining and Bioinformatics, Vol. 21, 2018, 123-144.
Osores, S.J.A., Ruz, G.A., Opitz, T., Lardies, M.A. Discovering divergence in the thermal physiology of intertidal crabs along latitudinal gradients using an integrated approach with machine learning, Journal of Thermal Biology, Vol. 78, 2018, 140-150.
Mascareño, A., Cordero, R., Azócar, G., Billi, M., Henríquez, P., Ruz, G.A. Controversies in social-ecological systems: lessons from a major red tide crisis in Chiloe Island, Chile, Ecology and Society, Vol. 23, 2018, 15.
Rengifo, F., Ruz, G.A., Mascareño, A. Managing the 1920s' Chilean educational crisis: A historical view combined with machine learning, PLoS ONE, 13(5), 2018, e0197429.
Di Genova, A., Ruz, G. A., Sagot, M.-F., Maass, A. Fast-SG: An alignment-free algorithm for hybrid assembly, GigaScience, Vol. 7, 2018, giy048.
Henríquez, P.A., Ruz, G.A. A non-iterative method for pruning hidden neurons in neural networks with random weights, Applied Soft Computing, Vol. 70, 2018, 1109-1121.
Valle, M.A., Ruz, G.A., Morrás, R. Market basket analysis: Complementing association rules with minimum spanning trees, Expert Systems With Applications, Vol. 97, 2018, 146-162.
Rodríguez-Valdecantos, G., Manzano, M., Sánchez, R., Urbina, F., Hengst, M.B., Lardies, M.A., Ruz, G.A., González, B. Early successional patterns of bacterial communities in soil microcosms reveal changes in bacterial community composition and network architecture, depending on the successional condition, Applied Soil Ecology, Vol. 120, 2017, 44-54.
Zúñiga, A., Donoso, R.A., Ruiz, D., Ruz, G.A., González, B. Quorum-sensing systems in the plant growth-promoting bacterium Paraburkholderia phytofirmans PsJN exhibit cross-regulation and are involved in biofilm formation, Molecular Plant-Microbe Interactions, Vol. 30, 2017, 557-565.
Valle, M.A., Ruz, G.A., Masías, V.H. Using self-organizing maps to model turnover of sales agents in a call center, Applied Soft Computing, Vol. 60, 2017, 763-774.
Henríquez, P.A., Ruz, G.A. Extreme learning machine with a deterministic assignment of hidden weights in two parallel layers, Neurocomputing, Vol. 226, 2017, 109-116.
Ruz, G.A. Improving the performance of inductive learning classifiers through the presentation order of the training patterns, Expert Systems with Applications, Vol. 58, 2016, 1-9.
Mascareño, A., Goles, E., Ruz, G.A. Crisis in Complex Social Systems: A Social Theory View Illustrated with the Chilean Case, Complexity, Vol. 21, No. S2, 2016, 13-23.
Valle, M.A., Ruz, G.A. Turnover prediction in a call center: behavioral evidence of loss aversion using random forest and naive Bayes algorithms, Applied Artificial Intelligence, Vol. 29, 2015, 923-942.
Valle, M.A., Ruz, G.A., Varas, S. Explaining job satisfaction and intentions to quit from a value-risk perspective, Academia Revista Latinoamericana de Administración, Vol. 28, 2015, 523-540.
Valle, M.A., Ruz, G.A., Varas, S. A Survival Model Based on Met Expectations: Application to Employee Turnover in a Call Center, Academia Revista Latinoamericana de Administración, Vol. 28, 2015, 177-194.
Goles, E., Ruz, G.A. Dynamics of neural networks over undirected graphs, Neural Networks, Vol. 63, 2015, 156-169.
Ruz, G.A., Timmermann, T., Barrera, J., Goles, E. Neutral space analysis for a Boolean network model of the fission yeast cell cycle network, Biological Research, Vol. 47, 2014, 64.
Ruz, G.A., Goles, E., Montalva, M., Fogel, G.B. Dynamical and Topological Robustness of the Mammalian Cell Cycle Network: A Reverse Engineering Approach, Biosystems, Vol. 115, 2014, 23-32.
Araya-Díaz, P., Ruz, G.A., Palomino, H.M. Discovering Craniofacial Patterns Using Multivariate Cephalometric Data for Treatment Decision Making in Orthodontics, International Journal of Morphology, Vol. 31, 2013, 1109-1115.
Ruz, G.A., Varas, S., Villena, M. Policy making for broadband adoption and usage in Chile through machine learning, Expert Systems with Applications, Vol. 40, 2013, 6728-6734.
Goles, E., Montalva, M., Ruz, G.A. Deconstruction and dynamical robustness of regulatory networks: application to the yeast cell cycle networks, Bulletin of Mathematical Biology, Vol. 75, 2013, 939-966.
Ruz, G. A. and Goles, E. Learning gene regulatory networks using the bees algorithm, Neural Computing & Applications, Vol. 22, 2013, 63-70.
Valle, M.A., Varas, S., Ruz, G.A. Job performance prediction in a call center using a naive Bayes classifier, Expert Systems with Applications, Vol. 39, 2012, 9939-9945.
Ruz, G. A. and Pham, D. T. NBSOM: The naive Bayes self-organizing map, Neural Computing & Applications, Vol. 21, 2012, 1319-1330.
Pham, D. T. and Ruz, G. A. Unsupervised training of Bayesian networks for data clustering, Proceedings of the Royal Society A, Vol. 465, 2009, 2927-2948.
Ruz, G.A. and Pham, D.T. Building Bayesian network classifiers through a Bayesian complexity monitoring system, Proc. IMechE, Part C: J. Mechanical Engineering Science, Vol. 223(C3), 2009, 743-755.
Ruz, G.A., Estévez, P.A. and Ramirez, P.A. Automated visual inspection system for wood defect classification using computational intelligence techniques, International Journal of Systems Science, Vol. 40, No. 2, February 2009,163-172.
Ruz, G.A., Estévez, P.A., Perez, C.A. A neurofuzzy color image segmentation method for wood surface defect detection, Forest Products Journal, Vol. 55, N 4, April 2005, 52-58.