A trans-dimensional Bayesian Markov chain Monte Carlo algorithm for model assessment using frequency-domain electromagnetic data

By B. Minsley. 2011

202 citations recorded by the source corpus.

Subfields: Geophysics, Ocean Engineering

View Paper: https://www.semanticscholar.org/paper/af1c948f9b0177a8dff7ae87f834f5aa9d0bef7b

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Geophysics

1. N. Rawlinson
2. Malcolm Sambridge
3. T. Bodin
4. Haim Waisman
5. Hao Sun
6. Anders Vest Christiansen
7. Esben Auken
8. P. Arroucau

In Ocean Engineering

1. Haim Waisman
2. Hao Sun
3. Malcolm Sambridge
4. Anders Vest Christiansen
5. Esben Auken
6. N. Rawlinson
7. T. Bodin
8. P. Arroucau

Citations in the corpus

• A guided Bayesian inference approach for detection of multiple flaws in structures using the extended finite element method (2015, background): “While determination of the convergence of a MCMC chain algorithm in a trans-dimensional manner is complicated and is still a subject of ongoing research [47,48], the sum of square errors defined in Eq.”
• A Global Measure for Depth of Investigation (2010, methodology): “This issue can only be addressed in full by the use of exhaustive methods like the MCMC discussed earlier (Minsley, 2011).”
• Transdimensional tomography with unknown data noise (2012, background): “…sciences and has been applied to a wide range of areas (e.g. Malinverno 2002; Stephenson et al. 2004, 2006; Jasra et al. 2006; Hopcroft et al. 2009; Charvin et al. 2009; Gallagher et al. 2011; Dettmer et al. 2010; Luo 2010; Piana Agostinetti & Malinverno 2010; Minsley 2011; Bodin et al. 2012).”