Pages that link to "Item:Q4743484"

The following pages link to Linear estimators and measurable linear transformations on a Hilbert space (Q4743484):

Displaying 35 items.

• On the functional Hodrick-Prescott filter with non-compact operators (Q254482) (← links)
• Oracle-type posterior contraction rates in Bayesian inverse problems (Q256079) (← links)
• Kriging for Hilbert-space valued random fields: the operatorial point of view (Q268732) (← links)
• The Bayesian formulation of EIT: analysis and algorithms (Q338599) (← links)
• A partial overview of the theory of statistics with functional data (Q389287) (← links)
• Computing the best linear predictor in a Hilbert space. Applications to general ARMAH processes (Q392108) (← links)
• A functional Hodrick-Prescott filter (Q522941) (← links)
• Nonparametric estimation of an instrumental regression: a quasi-Bayesian approach based on regularized posterior (Q528060) (← links)
• Bayesian inverse problems with Gaussian priors (Q661174) (← links)
• The Ornstein-Uhlenbeck bridge and applications to Markov semigroups (Q952823) (← links)
• Hierarchical Bayesian level set inversion (Q1703838) (← links)
• Importance sampling: intrinsic dimension and computational cost (Q1750255) (← links)
• On a generalization of the preconditioned Crank-Nicolson metropolis algorithm (Q1750384) (← links)
• Fractional-order regularization and wavelet approximation to the inverse estimation problem for random fields (Q1810713) (← links)
• The linear conditional expectation in Hilbert space (Q1983603) (← links)
• Higher order quasi-Monte Carlo integration for Bayesian PDE inversion (Q2203718) (← links)
• Wavelet-based priors accelerate maximum-a-posteriori optimization in Bayesian inverse problems (Q2218822) (← links)
• Best linear predictor of a \(C_{[0, 1]}\)-valued functional autoregressive process (Q2322611) (← links)
• Posterior contraction rates for the Bayesian approach to linear ill-posed inverse problems (Q2447734) (← links)
• Statistical inverse problems: discretization, model reduction and inverse crimes (Q2508956) (← links)
• SPDE bridges with observation noise and their spatial approximation (Q2689896) (← links)
• Regularized posteriors in linear ill-posed inverse problems (Q2911714) (← links)
• Gauss-Markov processes on Hilbert spaces (Q3448981) (← links)
• Analysis of the Ensemble and Polynomial Chaos Kalman Filters in Bayesian Inverse Problems (Q3452524) (← links)
• A deconvolution problem with the kernel 1/[x] on the plane (Q3772691) (← links)
• Posterior Contraction in Bayesian Inverse Problems Under Gaussian Priors (Q4554170) (← links)
• A Strongly Convergent Numerical Scheme from Ensemble Kalman Inversion (Q4581770) (← links)
• Iterative updating of model error for Bayesian inversion (Q4607829) (← links)
• Sparsity-promoting and edge-preserving maximum <i>a posteriori</i> estimators in non-parametric Bayesian inverse problems (Q4638174) (← links)
• A consistent estimator of the smoothing operator in the functional Hodrick–Prescott filter (Q5160235) (← links)
• Solving inverse problems using data-driven models (Q5230520) (← links)
• Optimal experimental design for infinite-dimensional Bayesian inverse problems governed by PDEs: a review (Q5854065) (← links)
• Uncertainty Quantification and Experimental Design for Large-Scale Linear Inverse Problems under Gaussian Process Priors (Q6109159) (← links)
• Convergence Rates for Learning Linear Operators from Noisy Data (Q6109175) (← links)
• A Hadamard fractional total variation-Gaussian (HFTG) prior for Bayesian inverse problems (Q6115634) (← links)