Pages that link to "Item:Q2508956"

The following pages link to Statistical inverse problems: discretization, model reduction and inverse crimes (Q2508956):

Displaying 50 items.

• Approximate marginalization of absorption and scattering in fluorescence diffuse optical tomography (Q254804) (← links)
• 4D-CT reconstruction with unified spatial-temporal patch-based regularization (Q256013) (← links)
• Compensation of domain modelling errors in the inverse source problem of the Poisson equation: application in electroencephalographic imaging (Q284924) (← links)
• Source identification in time domain electromagnetics (Q417878) (← links)
• Modelling of an oesophageal electrode for cardiac function tomography (Q428272) (← links)
• Approximate marginalization of unknown scattering in quantitative photoacoustic tomography (Q479892) (← links)
• Bayesian parameter identification for Turing systems on stationary and evolving domains (Q670616) (← links)
• Time-dependent current source identification for numerical simulations of Maxwell's equations (Q729192) (← links)
• Dimensionality reduction and polynomial chaos acceleration of Bayesian inference in inverse problems (Q1009939) (← links)
• Model reduction in state identification problems with an application to determination of thermal parameters (Q1012238) (← links)
• Discretization effects in statistical inverse problems (Q1174448) (← links)
• Proposition of a modal filtering method to enhance heat source computation within heterogeneous thermomechanical problems (Q1627080) (← links)
• Adjoint-accelerated statistical and deterministic inversion of atmospheric contaminant transport (Q1641495) (← links)
• Approximation error approach in spatiotemporally chaotic models with application to Kuramoto-Sivashinsky equation (Q1662815) (← links)
• Bayesian and variational Bayesian approaches for flows in heterogeneous random media (Q1692018) (← links)
• Statistical analysis of differential equations: introducing probability measures on numerical solutions (Q1703820) (← links)
• Estimating hemodynamic stimulus and blood vessel compliance from cerebral blood flow data (Q1716831) (← links)
• Where Bayes tweaks Gauss: conditionally Gaussian priors for stable multi-dipole estimation (Q1983459) (← links)
• An augmented time reversal method for source and scatterer identification (Q2002231) (← links)
• Damage identification under uncertain mass density distributions (Q2022028) (← links)
• Randomized reduced forward models for efficient Metropolis-Hastings MCMC, with application to subsurface fluid flow and capacitance tomography (Q2023287) (← links)
• Computed tomography reconstruction with uncertain view angles by iteratively updated model discrepancy (Q2033298) (← links)
• Accelerating the Bayesian inference of inverse problems by using data-driven compressive sensing method based on proper orthogonal decomposition (Q2055173) (← links)
• Limited-angle CT reconstruction with generalized shrinkage operators as regularizers (Q2063013) (← links)
• Infinite-dimensional inverse problems with finite measurements (Q2069717) (← links)
• Learning and correcting non-Gaussian model errors (Q2128493) (← links)
• Rate-optimal refinement strategies for local approximation MCMC (Q2172107) (← links)
• Particle filter-based data assimilation technique for the evaluation of transport of pollutants in small rivers (Q2204173) (← links)
• An additive approximation to multiplicative noise (Q2217386) (← links)
• Less is often more: applied inverse problems using \(hp\)-forward models (Q2222637) (← links)
• Accelerating uncertainty quantification of groundwater flow modelling using a deep neural network proxy (Q2237307) (← links)
• A Bayesian inference approach to identify a Robin coefficient in one-dimensional parabolic problems (Q2271971) (← links)
• Linear waveform tomography inversion using machine learning algorithms (Q2284092) (← links)
• Estimating the rate constant from biosensor data via an adaptive variational Bayesian approach (Q2291491) (← links)
• Sparse variational Bayesian approximations for nonlinear inverse problems: applications in nonlinear elastography (Q2414583) (← links)
• Convergence rates of accelerated proximal gradient algorithms under independent noise (Q2420162) (← links)
• A Bayesian linear model for the high-dimensional inverse problem of seismic tomography (Q2443172) (← links)
• Coordinate transformation and polynomial chaos for the Bayesian inference of a Gaussian process with parametrized prior covariance function (Q2631575) (← links)
• Bayesian neural network priors for edge-preserving inversion (Q2674903) (← links)
• Reliable and efficient parameter estimation using approximate continuum limit descriptions of stochastic models (Q2676029) (← links)
• Optical Imaging (Q2789818) (← links)
• Statistical Methods in Imaging (Q2789825) (← links)
• A stochastic simulation method for uncertainty quantification in the linearized inverse conductivity problem (Q2894981) (← links)
• Variational data assimilation using targetted random walks (Q2900440) (← links)
• System identification in tumor growth modeling using semi-empirical eigenfunctions (Q2911909) (← links)
• Reduced forward models in electrical impedance tomography with probe geometry (Q2949459) (← links)
• Estimation of fixed charge density and diffusivity profiles in cartilage using contrast enhanced computer tomography (Q2952469) (← links)
• Effects of a priori parameter selection in minimum relative entropy method on inverse electrocardiography problem (Q3122004) (← links)
• Estimation of simultaneous leakage flow rates and initial thermal state inside soil dikes through temperature measurements (Q3145103) (← links)
• Adaptive monotonicity method for permittivity imaging (Q3182816) (← links)