An adaptive hierarchical sparse grid collocation algorithm for the solution of stochastic differential equations X Ma, N Zabaras Journal of Computational Physics 228 (8), 3084-3113, 2009 | 498 | 2009 |

Sparse grid collocation schemes for stochastic natural convection problems B Ganapathysubramanian, N Zabaras Journal of Computational Physics 225 (1), 652-685, 2007 | 466 | 2007 |

A unified framework for the construction of one-step finite volume and discontinuous Galerkin schemes on unstructured meshes M Dumbser, DS Balsara, EF Toro, CD Munz Journal of Computational Physics 227 (18), 8209-8253, 2008 | 460 | 2008 |

An inverse method for determining elastic material properties and a material interface DS Schnur, N Zabaras International Journal for Numerical Methods in Engineering 33 (10), 2039-2057, 1992 | 283 | 1992 |

A Bayesian inference approach to the inverse heat conduction problem J Wang, N Zabaras International Journal of Heat and Mass Transfer 47 (17-18), 3927-3941, 2004 | 224 | 2004 |

An adaptive high-dimensional stochastic model representation technique for the solution of stochastic partial differential equations X Ma, N Zabaras Journal of Computational Physics 229 (10), 3884-3915, 2010 | 211 | 2010 |

Hierarchical Bayesian models for inverse problems in heat conduction J Wang, N Zabaras Inverse Problems 21 (1), 183, 2004 | 170 | 2004 |

Classification and reconstruction of three-dimensional microstructures using support vector machines V Sundararaghavan, N Zabaras Computational Materials Science 32 (2), 223-239, 2005 | 153 | 2005 |

A current density conservative scheme for incompressible MHD flows at a low magnetic Reynolds number. Part II: On an arbitrary collocated mesh MJ Ni, R Munipalli, P Huang, NB Morley, MA Abdou Journal of Computational Physics 227 (1), 205-228, 2007 | 150 | 2007 |

Using Bayesian statistics in the estimation of heat source in radiation J Wang, N Zabaras International Journal of Heat and Mass Transfer 48 (1), 15-29, 2005 | 146 | 2005 |

Finite element solution of two‐dimensional inverse elastic problems using spatial smoothing DS Schnur, N Zabaras International Journal for Numerical Methods in Engineering 30 (1), 57-75, 1990 | 142 | 1990 |

An efficient Bayesian inference approach to inverse problems based on an adaptive sparse grid collocation method X Ma, N Zabaras Inverse Problems 25 (3), 035013, 2009 | 139 | 2009 |

A sensitivity analysis for the optimal design of metal-forming processes S Badrinarayanan, N Zabaras Computer Methods in Applied Mechanics and Engineering 129 (4), 319-348, 1996 | 136 | 1996 |

Finite element analysis of some inverse elasticity problems A Maniatty, N Zabaras, K Stelson Journal of engineering mechanics 115 (6), 1303-1317, 1989 | 134 | 1989 |

Modeling diffusion in random heterogeneous media: Data-driven models, stochastic collocation and the variational multiscale method B Ganapathysubramanian, N Zabaras Journal of Computational Physics 226 (1), 326-353, 2007 | 124 | 2007 |

A level set simulation of dendritic solidification with combined features of front-tracking and fixed-domain methods L Tan, N Zabaras Journal of Computational Physics 211 (1), 36-63, 2006 | 124 | 2006 |

Bayesian deep convolutional encoder–decoder networks for surrogate modeling and uncertainty quantification Y Zhu, N Zabaras Journal of Computational Physics 366, 415-447, 2018 | 123 | 2018 |

Finite element analysis of progressive failure in laminated composite plates S Tolson, N Zabaras Computers & Structures 38 (3), 361-376, 1991 | 117 | 1991 |

Kernel principal component analysis for stochastic input model generation X Ma, N Zabaras Journal of Computational Physics 230 (19), 7311-7331, 2011 | 105 | 2011 |

A non-intrusive stochastic Galerkin approach for modeling uncertainty propagation in deformation processes S Acharjee, N Zabaras Computers & structures 85 (5-6), 244-254, 2007 | 105 | 2007 |