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Clayton Webster
Clayton Webster
Verified email at utexas.edu
Title
Cited by
Cited by
Year
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
13362008
Stochastic finite element methods for partial differential equations with random input data
MD Gunzburger, CG Webster, G Zhang
Acta Numerica 23, 521-650, 2014
735*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
7282008
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
6812016
Sparse collocation methods for stochastic interpolation and quadrature
M Gunzburger, CG Webster, G Zhang
Handbook of uncertainty quantification, 717-762, 2017
600*2017
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
237*2008
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
2342020
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
1652015
Design under uncertainty employing stochastic expansion methods
P Constatine, MS Eldred, CG Webster
International Journal for Uncertainty Quantification 1 (2), 2011
136*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
1172014
The Krein-Milman theorem in operator convexity
C Webster, S Winkler
Transactions of the American Mathematical Society 351 (1), 307-322, 1999
1071999
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
1022018
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
1002013
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
732014
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
73*1998
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
Quantifying the impact of single bit flips on floating point arithmetic
J Elliott, F Mueller, F Stoyanov, C Webster
North Carolina State University. Dept. of Computer Science, 2013
682013
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
66*2017
Sparse polynomial approximation of high-dimensional functions
B Adcock, S Brugiapaglia, CG Webster
SIAM, 2022
592022
Analysis of quasi-optimal polynomial approximations for parameterized PDEs with deterministic and stochastic coefficients
H Tran, CG Webster, G Zhang
Numerische Mathematik 137, 451-493, 2017
582017
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