Stochastic optimization with high-fidelity nonlinear models is often computationally prohibitive because each objective evaluation requires sampling-based uncertainty quantification inside an outer optimization loop. Multi-fidelity estimators, such as approximate control variates (ACV), can reduce this cost by exploiti...
Thomas E. Coons, Aniket Jivani, Xun Huan· 0 citations
Goal-oriented optimal experimental design (GO-OED) selects experiments according to the expected information gain (EIG) about a quantity of interest (QoI) rather than the full parameter vector. This work develops a variational GO-OED formulation for mixed discrete-continuous QoI laws arising in probabilistic mechanics...
Flood-monitoring sensors are often placed according to coverage, access, or expected inundation. However, the value of a measurement depends on the prediction or decision it is intended to inform. Using tRIBS-Urban simulations and a neural-network surrogate of the August 2014 metropolitan Detroit flood, we examine how...
Chen Cheng, V. Tran, Jiayuan Dong et al.· 0 citations
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