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Araujo, J., Ducoffe, G., Nisse, N., & Suchan, K. (2018). On interval number in cycle convexity. Discret. Math. Theor. Comput. Sci., 20(1), 35 pp.
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Chang, Q., Zhou, C. C., Valdebenito, M. A., Liu, H. W., & Yue, Z. F. (2022). A novel sensitivity index for analyzing the response of numerical models with interval inputs. Comput. Methods in Appl. Mech. Eng., 400, 115509.
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Dang, C., Wei, P. F., Faes, M. G. R., Valdebenito, M. A., & Beer, M. (2022). Interval uncertainty propagation by a parallel Bayesian global optimization method. Appl. Math. Model., 108, 220–235.
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de la Cruz, R., Salinas, H. S., & Meza, C. (2022). Reliability Estimation for Stress-Strength Model Based on Unit-Half-Normal Distribution. Symmetry, 14(4), 837.
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Faes, M. G. R., Valdebenito, M. A., Yuan, X. K., Wei, P. F., & Beer, M. (2021). Augmented reliability analysis for estimating imprecise first excursion probabilities in stochastic linear dynamics. Adv. Eng. Softw., 155, 102993.
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Goles, E., Slapnicar, I., & Lardies, M. A. (2021). Universal Evolutionary Model for Periodical Species. Complexity, 2021, 2976351.
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Leiva, V., Tejo, M., Guiraud, P., Schmachtenberg, O., Orio, P., & Marmolejo-Ramos, F. (2015). Modeling neural activity with cumulative damage distributions. Biol. Cybern., 109(4-5), 421–433.
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Osorio-Valenzuela, L., Pereira, J., Quezada, F., & Vasquez, O. C. (2019). Minimizing the number of machines with limited workload capacity for scheduling jobs with interval constraints. Appl. Math. Model., 74, 512–527.
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Yuan, X. K., Faes, M. G. R., Liu, S. L., Valdebenito, M. A., & Beer, M. (2021). Efficient imprecise reliability analysis using the Augmented Space Integral. Reliab. Eng. Syst. Saf., 210, 107477.
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