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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
12992008
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
7032008
Stochastic finite element methods for partial differential equations with random input data
MD Gunzburger, CG Webster, G Zhang
Acta Numerica 23, 521-650, 2014
702*2014
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
6242016
Sparse collocation methods for stochastic interpolation and quadrature
M Gunzburger, CG Webster, G Zhang
Handbook of uncertainty quantification, 1-46, 2017
530*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
234*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
1892020
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
1582015
Design under uncertainty employing stochastic expansion methods
P Constatine, MS Eldred, CG Webster
International Journal for Uncertainty Quantification 1 (2), 2011
130*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
1102014
The Krein-Milman theorem in operator convexity
C Webster, S Winkler
Transactions of the American Mathematical Society 351 (1), 307-322, 1999
1051999
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
962013
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
942018
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
70*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
672014
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
65*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
652013
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
63*2017
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
54*2015
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
532017
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