Simultaneous quantification of epistemic and aleatory uncertainty in GMPEs using Gaussian process regression

By Marcel Hermkes, N. Kuehn, Carsten Riggelsen. 2014

25 citations recorded by the source corpus.

Subfields: Building and Construction, Civil and Structural Engineering, Environmental Engineering

How researchers see this paper

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In Environmental Engineering

1. Federico Cerutti
2. Lance M. Kaplan

Citations in the corpus

• Rapid Trust Calibration through Interpretable and Uncertainty-Aware AI (2020, methodology): “A common approach is to use Bayesian methods, whereby epistemic uncertainty is captured as uncertainty in the model parameters(33) or as uncertainty in function space using, for example, Gaussian processes.(46) Another promising approach is that of evidential learning,(47,48) whereby inputs are mapp”