Pages that link to "Item:Q1951321"
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The following pages link to Gaussian Markov random field priors for inverse problems (Q1951321):
Displaying 19 items.
- Sampling-based uncertainty quantification in deconvolution of X-ray radiographs (Q491576) (← links)
- Hyperpriors for Matérn fields with applications in Bayesian inversion (Q667766) (← links)
- Likelihood-based estimation for Gaussian MRFs (Q713629) (← links)
- On the consistency of inversion-free parameter estimation for Gaussian random fields (Q739606) (← links)
- Multimodal, high-dimensional, model-based, Bayesian inverse problems with applications in biomechanics (Q1714421) (← links)
- The SPDE approach to Matérn fields: graph representations (Q2092895) (← links)
- Cauchy Markov random field priors for Bayesian inversion (Q2128078) (← links)
- Dealing with boundary artifacts in MCMC-based deconvolution (Q2341896) (← links)
- Sparse variational Bayesian approximations for nonlinear inverse problems: applications in nonlinear elastography (Q2414583) (← links)
- Cauchy difference priors for edge-preserving Bayesian inversion (Q2422503) (← links)
- Estimating Gaussian Markov random field parameters in a nonstationary framework: application to remote sensing imaging (Q4503267) (← links)
- Bayesian optical flow with uncertainty quantification (Q4582729) (← links)
- Estimating a pressure dependent thermal conductivity coefficient with applications in food technology (Q4991451) (← links)
- A blocking scheme for dimension-robust Gibbs sampling in large-scale image deblurring (Q5036782) (← links)
- Modeling material stress using integrated Gaussian Markov random fields (Q5037092) (← links)
- Error control of the numerical posterior with Bayes factors in Bayesian uncertainty quantification (Q6121680) (← links)
- A probabilistic, data-driven closure model for RANS simulations with aleatoric, model uncertainty (Q6553801) (← links)
- Bayesian inversion with Student's \(t\) priors based on Gaussian scale mixtures (Q6641742) (← links)
- Weak neural variational inference for solving Bayesian inverse problems \textit{without} forward models: applications in elastography (Q6663307) (← links)
