Machine learning‐accelerated gradient‐based Markov chain Monte Carlo inversion applied to electrical resistivity tomography-Reference-Cited by-同舟云学术

Machine learning‐accelerated gradient‐based Markov chain Monte Carlo inversion applied to electrical resistivity tomography

Published:2022-05-20 Issue:4 Volume:20 Page:440-461
ISSN:1569-4445
Container-title:Near Surface Geophysics
language:en
Short-container-title:Near Surface Geophysics

Author:

Aleardi Mattia¹^ORCID,Vinciguerra Alessandro¹²,Stucchi Eusebio¹,Hojat Azadeh³⁴

Affiliation:

1. University of Pisa Earth Sciences Department Pisa Italy

2. University of Florence Earth Sciences Department Florence Italy

3. Shahid Bahonar University of Kerman Department of Mining Engineering Kerman Iran

4. Politecnico di Milano Department of Civil and Environmental Engineering Milano Italy

Publisher

Wiley

Subject

Geophysics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/nsg.12211

Reference60 articles.

1. Inversion of synthetic and measured 3D geoelectrical data to study the geomembrane below a landfill;Aguzzoli A.;In 4th Asia Pacific Meeting on Near Surface Geoscience & Engineering,2021

2. Using orthogonal Legendre polynomials to parameterize global geophysical optimizations: Applications to seismic-petrophysical inversion and 1D elastic full-waveform inversion

3. Combining discrete cosine transform and convolutional neural networks to speed up the Hamiltonian Monte Carlo inversion of pre‐stack seismic data

4. Hamiltonian Monte Carlo algorithms for target- and interval-oriented amplitude versus angle inversions

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