19 citations · 20 across the 3 of their papers we have counts for
3 papers
stat.ME2025
Optimal Experimental Design Criteria for Data-Consistent Inversion
Troy Butler, John Jakeman, Michael Pilosov +2
The ability to design effective experiments is crucial for obtaining data that can substantially reduce the uncertainty in the predictions made using computational models. An optim…
stat.CO2017★ 19 cited
Optimal Experimental Design Using A Consistent Bayesian Approach
Scott N. Walsh, Tim M. Wildey, John D. Jakeman
We consider the utilization of a computational model to guide the optimal acquisition of experimental data to inform the stochastic description of model input parameters. Our formu…
math.NA2016★ 1 cited
Experimental Design : Optimizing Quantities of Interest to Reliably Reduce the Uncertainty in Model Input Parameters
Scott Walsh
As stakeholders and policy makers increasingly rely upon quantitative predictions from advanced computational models, a problem of fundamental importance is the quantification and…