Making global sensitivity analysis feasible using neural network surrogates

Today's article comes from the journal of Data-Centric Engineering. The authors are Weerasinghe et al., from the Arup Digital Technology Group, in the UK. In this paper they showcase a new way to make global sensitivity analysis practical and scalable without sacrificing fidelity.

DOI: 10.1017/dce.2025.10029

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