References
- N.L. Gibson, C. Gifford-Miears, A.S. Leon, and V.S. Vasylkivska, Efficient computation of unsteady flow in complex river systems with uncertain inputs, Int. J. Comput. Math. 91(4) (2014), pp. 781–797.
- E. Phipps, J. Hu, and J.T. Ostien, Exploring emerging many core architectures for uncertainty quantification through embedded stochastic Galerkin methods, Int. J. Comput. Math. 91(4) (2014), pp. 707–729.
- V. Rao, R. Archibald, and K.J. Evans, Emulation to simulate low-resolution atmospheric data, Int. J. Comput. Math. 91(4) (2014), pp. 770–780.
- O. Roderick, M. Anitescu, and Y. Peet, Proper orthogonal decompositions in multifidelity uncertainty quantification of complex simulation models, Int. J. Comput. Math. 91(4) (2014), pp. 748–769.
- S. Rohit, A. Patra, and V. Chaudhary, Integrating data and compute-intensive workflows for uncertainty quantification in large-scale simulation: Application to model-based hazard analysis, Int. J. Comput. Math. 91(4) (2014), pp. 730–747.
- C.G. Webster, G. Zhang, and M. Gunzburger, An adaptive sparse-grid iterative ensemble Kalman filter approach for parameter field estimation, Int. J. Comput. Math. 91(4) (2014), pp. 798–817.