Mixed linear-non-linear inversion of crustal deformation data: Bayesian inference of model, weighting and regularization parameters

By Junichi Fukuda, K. Johnson. 2010

86 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Geophysics

View Paper: https://www.semanticscholar.org/paper/7b44ed3d6a465115f2dfffac8da17f6ef6675c47

How researchers see this paper

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In Artificial Intelligence

1. A. Hooper
2. Marco Bagnardi

In Geophysics

1. A. Hooper
2. Marco Bagnardi

Citations in the corpus

• Inversion of Surface Deformation Data for Rapid Estimates of Source Parameters and Uncertainties: A Bayesian Approach (2018, methodology): “The application of a Bayesian approach when inverting geodetic data (e.g., Anderson & Segall, 2013; Fukuda & Johnson, 2010; Hooper et al., 2013; Jolivet et al., 2015; Minson et al., 2013) allows the characterization of posterior probability density functions (PDFs) of source parameters, which are…”