2021
DOI: 10.1093/gji/ggab034
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Accounting for theory errors with empirical Bayesian noise models in nonlinear centroid moment tensor estimation

Abstract: Summary Centroid moment-tensor (CMT) parameters can be estimated from seismic waveforms. Since these data indirectly observe the deformation process, CMTs are inferred as solutions to inverse problems which are generally under-determined and require significant assumptions, including assumptions about data noise. Broadly speaking, we consider noise to include both theory and measurement errors, where theory errors are due to assumptions in the inverse problem and measurement errors are caused by… Show more

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Cited by 35 publications
(18 citation statements)
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“…Although several Bayesian inversion approaches were recently developed to handle the uncertainties in finite fault inversion (e.g. Minson et al 2013;Shimizu et al 2020, Heimann et al 2018, including uncertainties related to Green's function (Yagi & Fukahata 2011, Vasyura-Bathke et al 2021, the effort of such methods is usually large which limits the approaches to the later detailed analysis long after the events.…”
Section: Introductionmentioning
confidence: 99%
“…Although several Bayesian inversion approaches were recently developed to handle the uncertainties in finite fault inversion (e.g. Minson et al 2013;Shimizu et al 2020, Heimann et al 2018, including uncertainties related to Green's function (Yagi & Fukahata 2011, Vasyura-Bathke et al 2021, the effort of such methods is usually large which limits the approaches to the later detailed analysis long after the events.…”
Section: Introductionmentioning
confidence: 99%
“…Some complexities such as layering or viscoelasticity can be accounted for (Amoruso et al, 2008) by using appropriate Green's functions for point dislocations (Okubo, 1993;Sun & Okubo, 1993;Wang et al, 2006). Besides, theory errors, arising from ignoring real Earth complexities, can be estimated in terms of noise covariance matrices within a Bayesian framework (see Duputel et al, 2014;Minson et al, 2013;Vasyura-Bathke et al, 2021).…”
Section: Discussionmentioning
confidence: 99%
“…Finally, errors in the Earth structure model can be taken into account for robust inference on the estimated source mechanism (Vasyura‐Bathke et al., 2021). The theory error from the choice of the 1‐D Earth structure model can be included in our framework by training and evaluating BNNs on each grid point for each Earth structure.…”
Section: Variational Inference Neural Network Estimation Of Mtsmentioning
confidence: 99%