Seismic tomography with the reversible jump algorithm

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Data‐driven spatial b value estimation with applications to California seismicity: To b or not to b (2015, methodology): “The method bears similarities with, and is in fact inspired by, the concept of transdimensional inference developed by Sambridge and others [Sambridge et al., 2006, 2013; Bodin and Sambridge, 2009].”
Resolution analysis in full waveform inversion (2011, methodology): “Approaches to the design of adaptive parametrizations mostly based on ray theory have been developed by various authors (e.g. Widiyantoro & van der Hilst 1997; Bijwaard et al. 1998; Boschi et al. 2004; Debayle & Sambridge 2004; Nolet & Montelli 2005; Bodin & Sambridge 2009; Schäfer et al. 2011).”
Estimation of trace gas fluxes with objectively determined basis functions using reversible jump Markov Chain Monte Carlo (2016, background): “For this special case it can be shown that the term | J | = 1 and so can be conveniently ignored (Bodin and Sambridge, 2009).”
On the use of sensitivity tests in seismic tomography (2016, positive): “Data adaptive parametrizations (e.g. Bijwaard et al. 1998; Spakman & Bijwaard 2001; Bodin & Sambridge 2009; Piana Agostinetti et al. 2015) attempt to minimize this effect, but most tomography is still carried out using static regular parametrizations.”