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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
13462008
Stochastic finite element methods for partial differential equations with random input data
MD Gunzburger, CG Webster, G Zhang
Acta Numerica 23, 521-650, 2014
745*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
7312008
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
7022016
Sparse collocation methods for stochastic interpolation and quadrature
M Gunzburger, CG Webster, G Zhang
Handbook of uncertainty quantification, 717-762, 2017
631*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
2482020
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
238*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
1692015
Design under uncertainty employing stochastic expansion methods
P Constatine, MS Eldred, CG Webster
International Journal for Uncertainty Quantification 1 (2), 2011
138*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
1202014
The Krein-Milman theorem in operator convexity
C Webster, S Winkler
Transactions of the American Mathematical Society 351 (1), 307-322, 1999
1091999
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
1032018
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
1012013
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
742014
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
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
702016
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
692013
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
642022
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
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