The Bayesian Approach to Inversion
Inversion of Surface Deformation Data for Rapid Estimates of Source Parameters and Uncertainties: A Bayesian Approach
... a Bayesian approach for the simultaneous inversion of independent geodetic data sets, in particular those from GNSS and InSAR, which takes into account errors in the data and prior information on ...
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A Bayesian Inference Approach to Reduce Uncertainty in Magnetotelluric Inversion: A Synthetic Case Study
... telluric Bayesian approach to examine non-linearity for the inverse ...luric inversion using a No-U-Turns ...developed Bayesian inversion code has low dependency on the in- itial model ...
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Hierarchical Bayesian level set inversion
... set approach has proven widely successful in the study of inverse problems for inter- faces, since its systematic development in the ...of Bayesian inversion, allowing for the quantification of ...
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Bayesian Induction of Bracketing Inversion Transduction Grammars
... novel Bayesian approach that attempts to find the maxi- mum a posteriori (MAP) or minimum description length (MDL) ...The approach iteratively segments the rules in a top-down fashion which al- lows ...
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Bayesian lithology–fluid inversion - algorithm efficiency
... the Bayesian approach; hence ratios larger than one does not mean that the approximate approach is better than the ex- act ...mate approach, regression towards the dominant classes is ...
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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 of ...
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MCMC and variational approaches for Bayesian inversion in diffraction imaging
... a Bayesian estimation framework. The Bayesian approach presented herein yields better results, both in microwave and optical imaging, than those obtained using deterministic iterative methods, such ...
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Parameter estimation via conditional expectation: a Bayesian inversion
... general approach for state and parameter estimation has been presented in a Bayesian ...The Bayesian approach is based here on the conditional expectation (CE) operator, and different ...
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Source reconstruction accuracy of MEG and EEG Bayesian inversion approaches.
... Variational Bayesian framework. A Bayesian approach to the Minimum Norm Model (MNM), an Empirical Bayesian Beamformer (EBB) and two iterative Bayesian schemes (Automatic Relevance ...
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Quantifying uncertainty in thermophysical properties of walls by means of Bayesian inversion
... The study from this subsection is particularly relevant in the context of lumped-thermal mass models [17, 16, 38] for Bayesian inference of a wall’s U-value and heat capacity per unit of area. Lumped-thermal mass ...
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Higher order quasi-Monte Carlo for Bayesian shape inversion
... Monte Carlo methods to a Bayesian approach for shape uncertainty quantification based on 604. a parametric partial di↵erential equation forward model[r] ...
29
Variational Bayesian inversion for hierarchical unsupervised generative embedding (HUGE)
... fully Bayesian approach that requires specifying priors for the various model parameters, raising the question how inference may depend on the particular choice of ...empirical Bayesian ...
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The Bayesian approach to inverse problems
... of Bayesian inversion on function space, leads to new sampling methods which are specifically tailored to the high dimensional problems which arise from discretization of the infinite dimensional ...
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Bayesian source inversion of microseismic events
... noise levels and for low uncertainty in the model, it is often negligible when estimating the source, much like the location uncertainty, but as the noise level increases or for large model uncertainties, the effect will ...
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A Bayesian method for microseismic source inversion
... source inversion (Reasenberg & Oppenheimer 1985; Hardebeck & Shearer 2002, 2003; Snoke ...several Bayesian approaches to source ...waveform inversion approaches ...the approach to ...
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Geostatistical approach to bayesian inversion of geophysical data: Markov chain Monte Carlo method
... Secondly, we think the Bayesian frame is an ongoing pro- cess of past, present and future states for the concerned re- gion. As in the saying, ‘Today’s posterior becomes tomor- row’s prior’, the solution in the ...
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A Bayesian partition modelling approach to resolve spatial variability in climate records from borehole temperature inversion
... the inversion methods used to reconstruct the past temperatures at each site must be mathematically identical and are therefore not necessarily best suited to all data ...a Bayesian partition model (BPM), ...
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Surrogate-assisted Bayesian inversion for landscape and basin evolution models
... hierarchical Bayesian model with two stages for MCMC sampling (Chib and Carlin, 1999; Wikle et ...learning approach where the knowledge from the past surrogate interval is utilized and refined with new ...
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Hierarchical Bayesian Inversion for the Point Source Moment Tensor: Method and Applications
... tensor inversion method in a probabilistic Bayesian framework that also accounts for noise in the ...source inversion using waveform data of moderate–size earthquakes and explosions at regional ...
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Point source moment tensor inversion through a Bayesian hierarchical model
... tensor inversion method in a probabilistic Bayesian framework that also accounts for noise in the ...source inversion using waveform data of moderate-size earthquakes and explosions at re- gional ...
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