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A general framework for quantifying uncertainty at scale
Quantifying uncertainty and performing sensitivity analysis in real-world, large-scale numerical simulations is virtually impossible with standard methods. We show that our recently developed sensitivity-driven sparse grid interpolation methods enables these two important tasks at scale.
A general framework for quantifying uncertainty at scale
Quantifying uncertainty and performing sensitivity analysis in real-world, large-scale numerical simulations is virtually impossible with standard methods. We show that our recently developed sensitivity-driven sparse grid interpolation methods enables these two important tasks at scale.
