| A sparse grid stochastic collocation method for partial differential equations with random input data F Nobile, R Tempone, CG Webster SIAM Journal on Numerical Analysis 46 (5), 2309-2345, 2008 | 1353 | 2008 |
| Stochastic finite element methods for partial differential equations with random input data MD Gunzburger, CG Webster, G Zhang Acta Numerica 23, 521-650, 2014 | 749* | 2014 |
| An anisotropic sparse grid stochastic collocation method for partial differential equations with random input data F Nobile, R Tempone, CG Webster SIAM Journal on Numerical Analysis 46 (5), 2411-2442, 2008 | 736 | 2008 |
| Deep learning for classification of malware system call sequences B Kolosnjaji, A Zarras, G Webster, C Eckert AI 2016: Advances in Artificial Intelligence: 29th Australasian Joint …, 2016 | 692 | 2016 |
| Sparse collocation methods for stochastic interpolation and quadrature M Gunzburger, CG Webster, G Zhang Handbook of uncertainty quantification, 717-762, 2017 | 647* | 2017 |
| Robotics, artificial intelligence, and the evolving nature of work C Webster, S Ivanov Digital transformation in business and society: Theory and cases, 127-143, 2020 | 248 | 2020 |
| Evaluation of non-intrusive approaches for Wiener-Askey generalized polynomial chaos P Constantine, MS Eldred, CG Webster Proceedings of the 10th AIAA Non-Deterministic Approaches Conference, number …, 2008 | 239* | 2008 |
| A multilevel stochastic collocation method for partial differential equations with random input data AL Teckentrup, P Jantsch, CG Webster, M Gunzburger SIAM/ASA Journal on Uncertainty Quantification 3 (1), 1046-1074, 2015 | 167 | 2015 |
| Design under uncertainty employing stochastic expansion methods P Constatine, MS Eldred, CG Webster International Journal for Uncertainty Quantification 1 (2), 2011 | 140* | 2011 |
| Applied mathematics research for exascale computing J Dongarra, J Hittinger, J Bell, L Chacon, R Falgout, M Heroux, P Hovland, ... Lawrence Livermore National Lab.(LLNL), Livermore, CA (United States), 2014 | 122 | 2014 |
| The Krein-Milman theorem in operator convexity C Webster, S Winkler Transactions of the American Mathematical Society 351 (1), 307-322, 1999 | 107 | 1999 |
| Polynomial approximation via compressed sensing of high-dimensional functions on lower sets A Chkifa, N Dexter, H Tran, C Webster Mathematics of Computation 87 (311), 1415-1450, 2018 | 103 | 2018 |
| An adaptive sparse‐grid high‐order stochastic collocation method for Bayesian inference in groundwater reactive transport modeling G Zhang, D Lu, M Ye, M Gunzburger, C Webster Water Resources Research 49 (10), 6871-6892, 2013 | 98 | 2013 |
| The effects of dust loadings on the collections of fine particles by an electrostatic precipitator with DC or pulse energized prechargers JS Chang, PC Looy, C Webster Journal of Aerosol Science 29, S1127-S1128, 1998 | 74* | 1998 |
| Doe advanced scientific computing advisory subcommittee (ascac) report: top ten exascale research challenges R Lucas, J Ang, K Bergman, S Borkar, W Carlson, L Carrington, G Chiu, ... USDOE Office of Science (SC)(United States), 2014 | 72 | 2014 |
| Quantifying the impact of single bit flips on floating point arithmetic JJ Elliott, F Mueller, MK Stoyanov, CG Webster Oak Ridge National Lab.(ORNL), Oak Ridge, TN (United States), 2013 | 70 | 2013 |
| A dynamically adaptive sparse grids method for quasi-optimal interpolation of multidimensional functions MK Stoyanov, CG Webster Computers & Mathematics with Applications 71 (11), 2449-2465, 2016 | 68* | 2016 |
| Compressed sensing approaches for polynomial approximation of high-dimensional functions B Adcock, S Brugiapaglia, CG Webster Compressed Sensing and its Applications: Second International MATHEON …, 2017 | 67* | 2017 |
| Sparse polynomial approximation of high-dimensional functions B Adcock, S Brugiapaglia, CG Webster SIAM, 2022 | 66 | 2022 |
| Numerical analysis of fixed point algorithms in the presence of hardware faults M Stoyanov, C Webster SIAM Journal on Scientific Computing 37 (5), C532-C553, 2015 | 61* | 2015 |
Guannan ZhangOak Ridge National LaboratoryVerified email at ornl.gov