Bayesian inversion applied to the observational results
Hierarchical Bayesian level set inversion
... hierarchical Bayesian level set framework is to infer a length-scale alongside with a level set function which, by means of expression (7), produces a discontinuous field that captures the desired piecewise ...
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Hierarchical Bayesian level set inversion
... aforementioned results we can also clearly see that the hierarchical MCMC algorithm produces similar outcomes regardless of the initialization of the inverse of the length-scale ⌧, reflecting ergodicity of the ...
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Bayesian source inversion of microseismic events
... the results from the amplitude ratios towards different source types and orientations, which may be an indicator of errors in the estimates rather than true non-double-couple ...
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A Bayesian method for microseismic source inversion
... This inversion produces samples from the source posterior probability distribution, including a best-fitting solution for the source mechanism and associated prob- ...The inversion can be constrained to the ...
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Bayesian lithology–fluid inversion - algorithm efficiency
... for inversion of seismic prestack AVO data into lithology-fluid classes in a vertical profile are ...The inversion is defined in a Bayesian set- ting where the prior model for the lithology-fluid ...
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Complexity analysis of accelerated MCMC methods for Bayesian inversion
... the Bayesian formulation [17, 29] is an attractive and natural one, because it allows for explicit incorporation of the statistical properties of the observational noise, because it admits the possibility ...
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MCMC and variational approaches for Bayesian inversion in diffraction imaging
... Both algorithms introduced herein are applied to two quite different configurations. The one related to microwave imaging is quasi-optimal: data are quasi-complete and frequency diverse. This means that the ...
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Dynamic models of brain imaging data and their Bayesian inversion
... model inversion and simulations that one can disambiguate between MFM and NMM models and found that the NMM was the best model for explaining MMN ...Our results suggest that the MFM captures the faster SEP ...
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Parameter estimation via conditional expectation: a Bayesian inversion
... obtain results which match the above theory as regards L -invariant subspaces, we shall assume that the set {ψ α } α∈ J M includes all the linear functions of ξ ...
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Fast Gibbs sampling for high-dimensional Bayesian inversion
... computed results in section ...in Bayesian inversion and section ...interesting results for Bayesian estimation in challenging, high-dimensional inverse problems ...theoretical ...
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Computational Bayesian techniques applied to cosmology
... Therefore 3 repetitions were performed, each using N live =500 with eff=0 . 01 (the repeat runs). The default July 2014 CosmoMC priors for the 20 CDM and nuisance parameters are used throughout with the priors mentioned ...
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Bayesian Methods applied to Reflection Seismology
... If we are looking for the velocity trend that best stacks the data, we have to find a way to compare different models according to the amount of information provided by them. During semblance analysis, the expert usually ...
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Bayesian estimation applied to multiple species
... i.e. we are dealing predominantly with type B data, we have a weight of 1=3. If it is easier to measure three photometric supernovae compared to one spectroscopic one, it will still be worth the effort in this case. We ...
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Source reconstruction accuracy of MEG and EEG Bayesian inversion approaches.
... ARD and GS employ different approaches to the recursive tuning on hyperparameters: ARD associates one hyperparameter to each source prior, while GS assigns the hyperparameters to source prior sets. A second important ...
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Quantifying uncertainty in thermophysical properties of walls by means of Bayesian inversion
... the Bayesian calibration of the HDM (with a relatively fine discretisation) allowed us to demonstrate that the proposed technique can (i) statistically detect unknown inhomogeneities within the wall; and (ii) ...
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Surrogate-assisted Bayesian inversion for landscape and basin evolution models
... Surrogate-assisted optimization has been used for several computationally expensive engineering problems which mo- tivate its use in optimization and inference of complex geo- scientific models. The use of surrogate ...
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Impact of petrophysical uncertainty on Bayesian hydrogeophysical inversion and model selection
... e Y , and the polynomial coefficients of the (d) constant, a 0 , (e) linear, a 1 and (f) quadratic, a 2 , terms describing the petrophysical relationships of Eqs. (9)-(11). Posterior distributions of the geostatistical ...
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Variational Bayesian inversion for hierarchical unsupervised generative embedding (HUGE)
... Variational Bayesian inversion for hierarchical unsupervised generative embedding (HUGE) Yao, Yu ; Raman, Sudhir S ; Schiek, Michael ; Leff, Alex ; Frässle, Stefan ; Stephan, Klaas E Abstract: A recently ...
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Joint inversion of seismic and electric data applied to 2D media
... Joint inversion of seismic and electric data applied to 2D media Flora Garofalo 1 , Guillaume Sauvin 2 , Laura Valentina Socco 1 , and Isabelle Lecomte 3 ABSTRACT Methods based on the seismic P-wave, ...
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An hybrid Imaging-Inversion method applied to potential fields data
... on inversion of the measured data, tends to be especially advantageous over the classical techniques when dealing with draped-to-level upward ...The inversion procedure involved in the meth- od implies ...
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