Approximation and error estimation in high dimensional space for stochastic collocation methods on arbitrary sparse samples
Conference
·
OSTI ID:1041437
- ORNL
We have develop a fast method that can capture piecewise smooth functions in high dimensions with high order and low computational cost. This method can be used for both approximation and error estimation of stochastic simulations where the computations can either be guided or come from a legacy database.
- Research Organization:
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). National Center for Computational Sciences (NCCS)
- Sponsoring Organization:
- USDOE Office of Science (SC)
- DOE Contract Number:
- DE-AC05-00OR22725
- OSTI ID:
- 1041437
- Resource Relation:
- Conference: Exascale Research Conference, Portland, OR, USA, 20120416, 20120416
- Country of Publication:
- United States
- Language:
- English
Similar Records
Error estimation in high dimensional space for stochastic collocation methods on arbitrary sparse samples
Error estimation in high dimensional space for stochastic collocation methods on arbitrary sparse samples
An adaptive hierarchical sparse grid collocation algorithm for the solution of stochastic differential equations
Conference
·
Tue Jan 01 00:00:00 EST 2013
·
OSTI ID:1041437
Error estimation in high dimensional space for stochastic collocation methods on arbitrary sparse samples
Conference
·
Tue Jan 01 00:00:00 EST 2013
·
OSTI ID:1041437
An adaptive hierarchical sparse grid collocation algorithm for the solution of stochastic differential equations
Journal Article
·
Fri May 01 00:00:00 EDT 2009
· Journal of Computational Physics
·
OSTI ID:1041437