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Armstrong, M., Valencia, J., Lagos, G., & Emery, X. (2022). Constructing Branching Trees of Geostatistical Simulations. Math. Geosci., Early Access.
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Aylwin, R., Jerez-Hanckes, C., Schwab, C., & Zech, J. (2020). Domain Uncertainty Quantification in Computational Electromagnetics. SIAM-ASA J. Uncertain. Quantif., 8(1), 301–341.
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Azar, M., Carrasco, R. A., & Mondschein, S. (2022). Dealing with Uncertain Surgery Times in Operating Room Scheduling. Eur. J. Oper. Res., 299(1), 377–394.
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Bergen, M., & Munoz, F. D. (2018). Quantifying the effects of uncertain climate and environmental policies on investments and carbon emissions: A case study of Chile. Energy Econ., 75, 261–273.
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Dang, C., Valdebenito, M. A., Faes, M. G. R., Wei, P. F., & Beer, M. (2022). Structural reliability analysis: A Bayesian perspective. Struct. Saf., 99, 102259.
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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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Dang, C., Wei, P. F., Faes, M. G. R., Valdebenito, M. A., & Beer, M. (2022). Parallel adaptive Bayesian quadrature for rare event estimation. Reliab. Eng. Syst. Saf., 225, 108621.
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Dölz, J., Harbrecht, H., Jerez-Hanckes, C., & Multerer M. (2022). Isogeometric multilevel quadrature for forward and inverse random acoustic scattering. Comput. Methods in Appl. Mech. Eng., 388, 114242.
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Escapil-Inchauspe, P., & Jerez-Hanckes, C. (2020). Helmholtz Scattering by Random Domains: First-Order Sparse Boundary Elements Approximation. SIAM J. Sci. Comput., 42(5), A2561–A2592.
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Fuenzalida, C., Jerez-Hanckes, C., & McClarren, R. G. (2019). Uncertainty Quantification For Multigroup Diffusion Equations Using Sparse Tensor Approximations. SIAM J. Sci. Comput., 41(3), B545–B575.
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Fustos-Toribio, I., Manque-Roa, N., Vasquez Antipan, D., Hermosilla Sotomayor, M., & Gonzalez, V. L. (2022). Rainfall-induced landslide early warning system based on corrected mesoscale numerical models: an application for the southern Andes. Nat. Hazards Earth Syst. Sci., 22(6), 2169–2183.
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Gordon, M. A., Vargas, F. J., & Peters, A. A. (2021). Comparison of Simple Strategies for Vehicular Platooning With Lossy Communication. IEEE Access, 9, 103996–104010.
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Guevara, E., Babonneau, F., Homem-de-Mello, T., & Moret, S. (2020). A machine learning and distributionally robust optimization framework for strategic energy planning under uncertainty. Appl. Energy, 271, 18 pp.
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Homem-de-Mello, T., Kong, Q. X., & Godoy-Barba, R. (2022). A Simulation Optimization Approach for the Appointment Scheduling Problem with Decision-Dependent Uncertainties. INFORMS J. Comput., Early Access.
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Lagos, G., Espinoza, D., Moreno, E., & Vielma, J. P. (2015). Restricted risk measures and robust optimization. Eur. J. Oper. Res., 241(3), 771–782.
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Ni, P. H., Jerez, D. J., Fragkoulis, V. C., Faes, M. G. R., Valdebenito, M. A., & Beer, M. (2022). Operator Norm-Based Statistical Linearization to Bound the First Excursion Probability of Nonlinear Structures Subjected to Imprecise Stochastic Loading. ASCE-ASME J. Risk Uncertain. Eng. Syst. A-Civ. Eng., 8(1), 04021086.
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O' Ryan, R., Benavides, C., Diaz, M., San Martin, J. P., & Mallea, J. (2019). Using probabilistic analysis to improve greenhouse gas baseline forecasts in developing country contexts: the case of Chile. Clim. Policy, 19(3), 299–314.
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Pereira, J. (2016). The robust (minmax regret) single machine scheduling with interval processing times and total weighted completion time objective. Comput. Oper. Res., 66, 141–152.
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Ramirez-Sagner, G., & Munoz, F. D. (2019). The effect of head-sensitive hydropower approximations on investments and operations in planning models for policy analysis. Renew. Sust. Energ. Rev., 105, 38–47.
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Reus, L., Belbeze, M., Feddersen, H., & Rubio, E. (2018). Extraction Planning Under Capacity Uncertainty at the Chuquicamata Underground Mine. Interfaces, 48(6), 543–555.
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