1 citations · 1 across the 1 of their papers we have counts for
3 papers
stat.ML2024
Local transfer learning Gaussian process modeling, with applications to surrogate modeling of expensive computer simulators
Xinming Wang, Simon Mak, John Miller +1
A critical bottleneck for scientific progress is the costly nature of computer simulations for complex systems. Surrogate models provide an appealing solution: such models are trai…
stat.AP2024
Expected Diverse Utility (EDU): Diverse Bayesian Optimization of Expensive Computer Simulators
John Joshua Miller, Simon Mak, Benny Sun +5
The optimization of expensive black-box simulators arises in a myriad of modern scientific and engineering applications. Bayesian optimization provides an appealing solution, by le…
stat.ML2024★ 1 cited
Targeted Variance Reduction: Robust Bayesian Optimization of Black-Box Simulators with Noise Parameters
John Joshua Miller, Simon Mak
The optimization of a black-box simulator over control parameters arises in a myriad of scientific applications. In such applications, the simulator often takes the fo…