48 skills found · Page 1 of 2
jenndrei / BayHunterMcMC transdimensional Bayesian inversion of surface wave dispersion and receiver functions
sebhaan / GeoboPython package for Multi-Objective Bayesian Optimisation and Joint Inversion
fmagrini / Bayes BayGeneralised Bayesian inversion framework
GeoscienceAustralia / HiQGA.jlHigh Quality Geophysical Analysis provides a general purpose Bayesian and deterministic inversion framework for various geophysical methods and spatially distributed / timeseries data
ruthamey / SlipBERIslipBERI is a matlab slip inversion code to solve for earthquake slip in a Bayesian fashion on a given fault plane, incorporating fractal properties through a von Karman prior. See Amey et al 2018: https://doi.org/10.1029/2017JB015316
jdhuang-csm / Bayes DrtHierarchical Bayesian methods for inversion of electrochemical impedance spectroscopy (EIS) data
latz-io / Bayesian InversionA collection of algorithms used in Bayesian Statistics and particularly in Bayesian Inverse Problems. This repository also contains some further material, like an incomplete short review on Bayesian Inverse Problems and Slides concerning BIPs.
mattdunlop / Bayes HierMATLAB MCMC for Bayesian hierarchical inversion
liaoweiyang2017 / TransMTMPIThis code is used for MT MPI prallel temperature sampling Bayesian inversion.
izzatum / Langevin GJI 2020Bayesian seismic inversion: Fast sampling Langevin dynamics Markov chain Monte Carlo
Tom-900 / Bayesian Semi Supervised Impedance InversionSemi-supervised Impedance Inversion by Bayesian Neural Network Based on 2-d CNN Pre-training
hongbo-yao / BayesMTGDSTrans-dimensional Bayesian joint inversion of magnetotelluric and geomagnetic depth sounding responses to constrain mantle electrical discontinuities
MongHanHuang / THB RjMCMCA transdimensional hierarchical Bayesian reversible jump Markov chain Monte Carlo method for active source seismic refraction inversions
KaiyuanZh / CENSOR[NDSS 2025] CENSOR: Defense Against Gradient Inversion via Orthogonal Subspace Bayesian Sampling
ejhgeo / BayGrav3DBayGrav3D is a Bayesian linear gravity inverse modeling program that inverts gravity data to determine the best-fitting densities of spatially discretized 3D subsurface prisms in a least-squares sense. We use a Bayesian approach to incorporate both data uncertainty and prior geophysical constraints, such as seismic data. Gaussian priors are applied to the model parameters as absolute equality constraints. BayGrav3D utilizes Tikhonov regularization as a relative equality constraint that smooths and stabilizes the inversion solution. Given gravity data and a set of priors, the inversion produces a solution to the model parameters (i.e. density) and the full covariance and resolution matrices to quantify the error on the solution. BayGrav3D is capable of working on both local and regional scales and with both simple and complex subsurface geometries. BayGrav3D is written is Matlab, and the release contains an example project with data with which users may test the scripts. A python release is planned sometime in the coming year or so. For more information on the methods, please refer to our paper - Hightower et al. (2020), A Bayesian 3-D linear gravity inversion for complex density distributions: application to the Puysegur subduction system, GJI, v. 223, p. 1899-1918. For using the program, please refer to the documentation (soon to be available on ReadTheDocs) and the commentary within the scripts.
CUG-EMI / TransdEMA software package for transdimensional Bayesian inversion of electromagnetic data over horizontally stratified media.
clberube / BISIPBISIP | Bayesian inversion of spectral induced polarization laboratory data
jdhuang-csm / Bayes Drt2Hierarchical Bayesian inversion of electrochemical impedance spectroscopy (EIS) data
pierrePalud / BeetrootsBeetroots (BayEsian invErsion with spaTial Regularization of nOisy multi-line ObservaTion mapS) is a Python package that performs Bayesian inference with the sampling algorithm described in (Palud et al., 2023).
mbaltieri / GeneralisedFilteringGeneral framework for Bayesian inversion of continuous hierarchical models
