4 citations · 4 across the 2 of their papers we have counts for
2 papers
math.NA2024
Adaptive Gradient Enhanced Gaussian Process Surrogates for Inverse Problems
Phillip Semler, Martin Weiser
Generating simulated training data needed for constructing sufficiently accurate surrogate models to be used for efficient optimization or parameter identification can incur a huge…
math.NA2023★ 4 cited
Adaptive Gaussian Process Regression for Efficient Building of Surrogate Models in Inverse Problems
Phillip Semler, Martin Weiser
In a task where many similar inverse problems must be solved, evaluating costly simulations is impractical. Therefore, replacing the model with a surrogate model that can…