2 papers
stat.ME2024
Parametric multi-fidelity Monte Carlo estimation with applications to extremes
Minji Kim, Brendan Brown, Vladas Pipiras
In a multi-fidelity setting, data are available from two sources, high- and low-fidelity. Low-fidelity data has larger size and can be leveraged to make more efficient inference ab…
stat.ME2024
Sampling low-fidelity outputs for estimation of high-fidelity density and its tails
Minji Kim, Kevin O'Connor, Vladas Pipiras +1
In a multifidelity setting, data are available under the same conditions from two (or more) sources, e.g. computer codes, one being lower-fidelity but computationally cheaper, and…