Characterising harmful data sources when constructing multi-fidelity surrogate models

arXiv:2403.08118v1 Announce Type: cross
Abstract: Surrogate modelling techniques have seen growing attention in recent years when applied to both modelling and optimisation of industrial design problems. These techniques are highly relevant when assessing the performance of a particular design carries a high cost, as the overall cost can be mitigated via the construction of a model to be queried in lieu of the available high-cost source. The construction of these models can sometimes employ other sources of information which are …

abstract arxiv attention cost cs.ai cs.lg data data sources design fidelity industrial modelling optimisation performance stat.me stat.ml type via