Multi-fidelity Gaussian process surrogate modeling for regression
problems in physics
Multi-fidelity Gaussian process surrogate modeling for regression
problems in physics
One of the main challenges in surrogate modeling is the limited availability of data due to resource constraints associated with computationally expensive simulations. Multi-fidelity methods provide a solution by chaining models in a hierarchy with increasing fidelity, associated with lower error, but increasing cost. In this paper, we compare different …