UB Paderborn / Katalog / Suche / in CDI

Bayesian Gaussian Mixture Linear Inversion for Geophysical Inverse Problems

Mathematical geosciences, 2017-05, Vol.49 (4), p.493-515

2017

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Blind Categorical Deconvolution in Two-Level Hidden Markov Models

IEEE transactions on geoscience and remote sensing, 2014-11, Vol.52 (11), p.7435-7447

2014

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Data Assimilation in Spatio-Temporal Models with Non-Gaussian Initial States—The Selection Ensemble Kalman Model

Applied sciences, 2020-09, Vol.10 (17), p.5742

2020

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Spatio-Temporal Inversion Using the Selection Kalman Model

Frontiers in applied mathematics and statistics, 2021-04, Vol.7

2021

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Bayesian Inversion of Convolved Hidden Markov Models With Applications in Reservoir Prediction

IEEE transactions on geoscience and remote sensing, 2020-03, Vol.58 (3), p.1957-1968

2020

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Inference of the Transition Matrix in Convolved Hidden Markov Models and the Generalized Baum-Welch Algorithm

IEEE transactions on geoscience and remote sensing, 2015-12, Vol.53 (12), p.6443-6456

2015

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Bayesian Inversion of Time-Lapse Seismic AVO Data for Multimodal Reservoir Properties

IEEE transactions on geoscience and remote sensing, 2021-11, Vol.59 (11), p.9104-9119

2021

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Bayesian Seismic AVO Inversion Using a Laterally Coupled Multimodal Prior Model

IEEE transactions on geoscience and remote sensing, 2022, Vol.60, p.1-16

2022

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Approximate posterior distributions for convolutional two-level hidden Markov models

Computational statistics & data analysis, 2013-02, Vol.58, p.187-200

2013

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Bayesian Spatial Inversion and Conjugate Selection Gaussian Prior Models

SIAM/ASA journal on uncertainty quantification, 2021-01, Vol.9 (2), p.420-445

2021

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Skew-Gaussian random fields

Spatial statistics, 2014-11, Vol.10, p.43-62

2014

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Inference of the Transition Matrix in Convolved Hidden Markov Models and the Generalized Bau-Welch Algorithm

IEEE transactions on geoscience and remote sensing, 2015-12, Vol.53 (12), p.6443

2015

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Bayesian Inversion in Hidden Markov Models with Varying Marginal Proportions

Mathematical geosciences, 2019-05, Vol.51 (4), p.463-484

2019

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Localized/Shrinkage Kriging Predictors

Mathematical geosciences, 2016-07, Vol.48 (5), p.595-618

2016

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T-distributed Random Fields: A Parametric Model for Heavy-tailedWell-log Data1

Mathematical geology, 2006-10, Vol.38 (7), p.821-849

2006

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Uncertainty Quantification in the Ensemble Kalman Filter

Scandinavian journal of statistics, 2013-12, Vol.40 (4), p.868-885

2013

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Estimation of a non‐stationary prior covariance from seismic data

Geophysical Prospecting, 2020-02, Vol.68 (2), p.393-410

2020

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Inversion of well logs into lithology classes accounting for spatial dependencies by using hidden markov models and recurrent neural networks

Journal of petroleum science & engineering, 2021-01, Vol.196, p.107598, Article 107598

2021

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Resampling the ensemble Kalman filter

Computers & geosciences, 2013-06, Vol.55, p.44-53

2013

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Ensemble Kalman filtering with shrinkage regression techniques

Computational geosciences, 2011-03, Vol.15 (2), p.271-292

2011

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T-distributed random fields : A parametric model for heavy-tailed well-log data

Mathematical geology, 2006-11, Vol.38 (7), p.821-849

2006

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Ensemble Kalman filtering for non-linear likelihood models using kernel-shrinkage regression techniques

Computational geosciences, 2011-06, Vol.15 (3), p.529-544

2011

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Bayesian lithology/fluid prediction constrained by spatial couplings and rock physics depth trends

Leading edge (Tulsa, Okla.), 2010-05, Vol.29 (5), p.584-589

2010

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Joint AVO inversion, wavelet estimation and noise-level estimation using a spatially coupled hierarchical Bayesian model

Geophysical Prospecting, 2003-11, Vol.51 (6), p.531-550

2003

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Bayesian Inversion of Piecewise Affine Operators in a Gaussian Framework

Journal of computational and graphical statistics, 2005-03, Vol.14 (1), p.56-74

2005

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Einstellungen

Bayesian Gaussian Mixture Linear Inversion for Geophysical Inverse Problems

Blind Categorical Deconvolution in Two-Level Hidden Markov Models

Data Assimilation in Spatio-Temporal Models with Non-Gaussian Initial States—The Selection Ensemble Kalman Model

Spatio-Temporal Inversion Using the Selection Kalman Model

Bayesian Inversion of Convolved Hidden Markov Models With Applications in Reservoir Prediction

Inference of the Transition Matrix in Convolved Hidden Markov Models and the Generalized Baum-Welch Algorithm

Bayesian Inversion of Time-Lapse Seismic AVO Data for Multimodal Reservoir Properties

Bayesian Seismic AVO Inversion Using a Laterally Coupled Multimodal Prior Model

Approximate posterior distributions for convolutional two-level hidden Markov models

Bayesian Spatial Inversion and Conjugate Selection Gaussian Prior Models

Skew-Gaussian random fields

Inference of the Transition Matrix in Convolved Hidden Markov Models and the Generalized Bau-Welch Algorithm

Bayesian Inversion in Hidden Markov Models with Varying Marginal Proportions

Localized/Shrinkage Kriging Predictors

T-distributed Random Fields: A Parametric Model for Heavy-tailedWell-log Data1

Uncertainty Quantification in the Ensemble Kalman Filter

Estimation of a non‐stationary prior covariance from seismic data

Inversion of well logs into lithology classes accounting for spatial dependencies by using hidden markov models and recurrent neural networks

Resampling the ensemble Kalman filter

Ensemble Kalman filtering with shrinkage regression techniques

T-distributed random fields : A parametric model for heavy-tailed well-log data

Ensemble Kalman filtering for non-linear likelihood models using kernel-shrinkage regression techniques

Bayesian lithology/fluid prediction constrained by spatial couplings and rock physics depth trends

Joint AVO inversion, wavelet estimation and noise-level estimation using a spatially coupled hierarchical Bayesian model

Bayesian Inversion of Piecewise Affine Operators in a Gaussian Framework

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