Bayesian Surrogate Training on Multiple Data Sources: A Hybrid Modeling Strategy

ArXi:2412.11875v3 Announce Type: replace-cross Surrogate models are often used as computationally efficient approximations to complex simulation models, enabling tasks such as solving inverse problems, sensitivity analysis, and probabilistic forward predictions, which would otherwise be computationally infeasible. During