IR Tools
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Source code repository: https://github.com/jnagy1/IRtools
Related Items (57)
Regularization properties of Krylov iterative solvers CGME and LSMR for linear discrete ill-posed problems with an application to truncated randomized SVDs ⋮ On non-parametric density estimation on linear and non-linear manifolds using generalized Radon transforms ⋮ Error estimates for Golub–Kahan bidiagonalization with Tikhonov regularization for ill–posed operator equations ⋮ Direct Implementation of Tikhonov Regularization for the First Kind Integral Equation ⋮ Golub-Kahan vs. Monte Carlo: a comparison of bidiagonlization and a randomized SVD method for the solution of linear discrete ill-posed problems ⋮ Generalized cross validation for \(\ell^p\)-\(\ell^q\) minimization ⋮ Graph Laplacian for image deblurring ⋮ Anymatrix: an extensible MATLAB matrix collection ⋮ An Arnoldi-based preconditioner for iterated Tikhonov regularization ⋮ Adaptive cross approximation for Tikhonov regularization in general form ⋮ Numerical methods for CT reconstruction with unknown geometry parameters ⋮ A joint bidiagonalization based iterative algorithm for large scale general-form Tikhonov regularization ⋮ Solution of ill-posed problems with Chebfun ⋮ Modulus-based iterative methods for constrained ℓ p – ℓ q minimization ⋮ Regularization properties of LSQR for linear discrete ill-posed problems in the multiple singular value case and best, near best and general low rank approximations ⋮ Nonlinear optimization for mixed attenuation polyenergetic image reconstruction ⋮ An inner–outer iterative method for edge preservation in image restoration and reconstruction * ⋮ Projected Newton method for noise constrained ℓ p regularization ⋮ Column-oriented algebraic iterative methods for nonnegative constrained least squares problems ⋮ Microlocal Analysis of a Compton Tomography Problem ⋮ Mathematical modeling for 2D light-sheet fluorescence microscopy image reconstruction ⋮ Krylov Methods for Low-Rank Regularization ⋮ An ADMM-LAP method for total variation myopic deconvolution of adaptive optics retinal images ⋮ Regularization of inverse problems by an approximate matrix-function technique ⋮ Singular Value Decomposition Approximation via Kronecker Summations for Imaging Applications ⋮ Hybrid Projection Methods with Recycling for Inverse Problems ⋮ Relaxed Regularization for Linear Inverse Problems ⋮ Variational networks: an optimal control approach to early stopping variational methods for image restoration ⋮ ADMM-softmax: an ADMM approach for multinomial logistic regression ⋮ A multigrid frame based method for image deblurring ⋮ A linear state space model for photoacoustic imaging in an acoustic attenuating media ⋮ Iteratively Reweighted FGMRES and FLSQR for Sparse Reconstruction ⋮ The regularizing properties of global GMRES for solving large-scale linear discrete ill-posed problems with several right-hand sides ⋮ A novel modified TRSVD method for large-scale linear discrete ill-posed problems ⋮ Unbiased predictive risk estimation of the Tikhonov regularization parameter: convergence with increasing rank approximations of the singular value decomposition ⋮ Unnamed Item ⋮ Flexible GMRES for total variation regularization ⋮ Pocket guide to solve inverse problems with GlobalBioIm ⋮ Linearized Krylov subspace Bregman iteration with nonnegativity constraint ⋮ Structured FISTA for image restoration ⋮ A simplified L-curve method as error estimator ⋮ Approximation accuracy of the Krylov subspaces for linear discrete ill-posed problems ⋮ Randomized core reduction for discrete ill-posed problem ⋮ Hybrid enriched bidiagonalization for discrete ill‐posed problems ⋮ Fast alternating direction multipliers method by generalized Krylov subspaces ⋮ Arnoldi decomposition, GMRES, and preconditioning for linear discrete ill-posed problems ⋮ LAP: a Linearize and Project Method for Solving Inverse Problems with Coupled Variables ⋮ Flexible Krylov Methods for $\ell_p$ Regularization ⋮ Hybrid Projection Methods with Recycling for Inverse Problems ⋮ Relaxed Regularization for Linear Inverse Problems ⋮ The low rank approximations and Ritz values in LSQR for linear discrete ill-posed problem ⋮ Projected Newton method for noise constrained Tikhonov regularization ⋮ On Krylov solutions to infinite-dimensional inverse linear problems ⋮ Hybrid projection methods for large-scale inverse problems with mixed Gaussian priors ⋮ Limited-Angle CT Reconstruction via the $L_1/L_2$ Minimization ⋮ Subspace Recycling--Based Regularization Methods ⋮ Single-pass randomized QLP decomposition for low-rank approximation
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