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Solving inverse problems using data-driven models (Q5230520)

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scientific article; zbMATH DE number 7099159

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English	Solving inverse problems using data-driven models	scientific article; zbMATH DE number 7099159

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scholarly article

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Solving inverse problems using data-driven models (English)

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zbMATH Open document ID

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10.1017/S0962492919000059

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Carola-Bibiane Schönlieb

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Simon R. Arridge

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publication date

28 August 2019

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Mathematics Subject Classification ID

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zbMATH DE Number

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describes a project that uses

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compsensing_dip

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DeepAdverserialRegulariser

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Wasserstein GAN

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convex_learning

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MaRDI profile type

MaRDI publication profile

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Generalized sampling and infinite-dimensional compressed sensing

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Solving ill-posed inverse problems using iterative deep neural networks

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Task adapted reconstruction for inverse problems

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Posterior contraction rates for the Bayesian approach to linear ill-posed inverse problems

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Bayesian posterior contraction rates for linear severely ill-posed inverse problems

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$rm K$-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation

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Multi-scale geometric methods for data sets. II: Geometric multi-resolution analysis

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Extraction of Digital Wavefront Sets Using Applied Harmonic Analysis and Deep Neural Networks

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Optical tomography: forward and inverse problems

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A Data-Driven Iteratively Regularized Landweber Iteration

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Remarks on choosing a regularization parameter using the quasi-optimality and ratio criterion

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Ultrasound Modulated Bioluminescence Tomography and Controllability of the Radiative Transport Equation

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On the Optimality of Conditional Expectation as a Bregman Predictor

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Data-Driven Nonsmooth Optimization

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Approximation and estimation bounds for artificial neural networks

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Fully smoothed \(\ell_1\)-\(TV\) models: bounds for the minimizers and parameter choice

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Convex analysis and monotone operator theory in Hilbert spaces

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A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems

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An Alternating Semiproximal Method for Nonconvex Regularized Structured Total Least Squares Problems

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Modern regularization methods for inverse problems

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Higher-order TV methods -- enhancement via Bregman iteration

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The study of an iterative method for the reconstruction of images corrupted by Poisson and Gaussian noise

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Statistical decision theory and Bayesian analysis. 2nd ed

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Large‐Scale Inverse Problems and Quantification of Uncertainty

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Convergence Rates of General Regularization Methods for Statistical Inverse Problems and Applications

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A double regularization approach for inverse problems with noisy data and inexact operator

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Compressed Sensing With Nonlinear Observations and Related Nonlinear Optimization Problems

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Iterative thresholding for sparse approximations

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Consistency of the posterior distribution in generalized linear inverse problems

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Optimal Approximation with Sparsely Connected Deep Neural Networks

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Pontryagin's principle in the control of semilinear elliptic variational inequalities

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On the convergence rate of a forward-backward type primal-dual splitting algorithm for convex optimization problems

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A Douglas--Rachford Type Primal-Dual Method for Solving Inclusions with Mixtures of Composite and Parallel-Sum Type Monotone Operators

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Optimization Methods for Large-Scale Machine Learning

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Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers

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Total Generalized Variation

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Properties of \(L^{1}-TGV^{2}\) : The one-dimensional case

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A generalized conditional gradient method and its connection to an iterative shrinkage method

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Consistent Estimates and Zero-One Sets

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From Sparse Solutions of Systems of Equations to Sparse Modeling of Signals and Images

0 references

A Review of Image Denoising Algorithms, with a New One

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Learning the invisible: a hybrid deep learning-shearlet framework for limited angle computed tomography

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A Semiblind Regularization Algorithm for Inverse Problems with Application to Image Deblurring

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Model Reduction for Large-Scale Systems with High-Dimensional Parametric Input Space

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Maximum<i>a posteriori</i>estimates in linear inverse problems with log-concave priors are proper Bayes estimators

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Sample size selection in optimization methods for machine learning

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Bilevel approaches for learning of variational imaging models

0 references

Dynamic Sampling Schemes for Optimal Noise Learning Under Multiple Nonsmooth Constraints

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Infimal Convolution of Data Discrepancies for Mixed Noise Removal

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Uniqueness in the Cauchy Problem for Partial Differential Equations

0 references

On the existence of certain singular integrals

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On Singular Integrals

0 references

Hypermodels in the Bayesian imaging framework

0 references

On the regularizing properties of the GMRES method

0 references

Hierachical Bayesian models and sparsity: <i>ℓ</i> <sub>2</sub> -magic

0 references

Continuous curvelet transform. I: Resolution of the wavefront set

0 references

Fast Computation of Fourier Integral Operators

0 references

Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information

0 references

0 references

Nonparametric Bernstein-von Mises theorems in Gaussian white noise

0 references

On the Bernstein-von Mises phenomenon for nonparametric Bayes procedures

0 references

Image recovery via total variation minimization and related problems

0 references

A first-order primal-dual algorithm for convex problems with applications to imaging

0 references

An introduction to continuous optimization for imaging

0 references

A convex variational model for learning convolutional image atoms from incomplete data

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Image Processing and Analysis

0 references

0 references

Insights Into Analysis Operator Learning: From Patch-Based Sparse Models to Higher Order MRFs

0 references

Learning regularization parameters for general-form Tikhonov

0 references

Generalized Modes in Bayesian Inverse Problems

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Compressed sensing and best 𝑘-term approximation

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Proximal Splitting Methods in Signal Processing

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Primal-dual splitting algorithm for solving inclusions with mixtures of composite, Lipschitzian, and parallel-sum type monotone operators

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Signal Recovery by Proximal Forward-Backward Splitting

0 references

0 references

Approximation by superpositions of a sigmoidal function

0 references

MAP estimators and their consistency in Bayesian nonparametric inverse problems

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An iterative thresholding algorithm for linear inverse problems with a sparsity constraint

0 references

Ten Lectures on Wavelets

0 references

The Ill-Conditioned Nature of the Limited Angle Tomography Problem

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One dimensional fractional order TGV: gamma-convergence and bilevel training scheme

0 references

On Row Relaxation Methods for Large Constrained Least Squares Problems

0 references

Optimal Control of a Class of Variational Inequalities of the Second Kind

0 references

Numerical PDE-Constrained Optimization

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Image denoising: learning the noise model via nonsmooth PDE-constrained optimization

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The structure of optimal parameters for image restoration problems

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Bilevel parameter learning for higher-order total variation regularisation models

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Singular value decomposition and its application to numerical inversion for ray transforms in 2D vector tomography

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Regularization by architecture: a deep prior approach for inverse problems

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Tailfree and neutral random probabilities and their posterior distributions

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Image restoration via simultaneous sparse coding: where structured sparsity meets Gaussian scale mixture

0 references

Nonlocally Centralized Sparse Representation for Image Restoration

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Image Deblurring and Super-Resolution by Adaptive Sparse Domain Selection and Adaptive Regularization

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Sparse Solution of Underdetermined Systems of Linear Equations by Stagewise Orthogonal Matching Pursuit

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0 references

Performance of first-order methods for smooth convex minimization: a novel approach

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Efficient Bayesian Computation by Proximal Markov Chain Monte Carlo: When Langevin Meets Moreau

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Deep learning-based numerical methods for high-dimensional parabolic partial differential equations and backward stochastic differential equations

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On the Douglas-Rachford splitting method and the proximal point algorithm for maximal monotone operators

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Sparse and Redundant Representations

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Convergence rates for Tikhonov regularisation of non-linear ill-posed problems

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Inverse problems as statistics

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Inversion of cone-beam data and helical tomography

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Iterative thresholding algorithms

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Dictionary-sparse recovery via thresholding-based algorithms

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A mathematical introduction to compressive sensing

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On the Asymptotic Behavior of Bayes' Estimates in the Discrete Case

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Fast CG-Based Methods for Tikhonov--Phillips Regularization

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First- and Second-Order Methods for Online Convolutional Dictionary Learning

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Fundamentals of Nonparametric Bayesian Inference

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Posterior consistency of Dirichlet mixtures in density estimation

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Convergence rates of posterior distributions.

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Nonlocal Operators with Applications to Image Processing

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Bernstein--von Mises Theorems and Uncertainty Quantification for Linear Inverse Problems

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Riemann Manifold Langevin and Hamiltonian Monte Carlo Methods

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Tradeoffs Between Convergence Speed and Reconstruction Accuracy in Inverse Problems

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An Analysis of the Total Least Squares Problem

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Tikhonov Regularization and Total Least Squares

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Generalized Cross-Validation as a Method for Choosing a Good Ridge Parameter

0 references

Sparse regularization with <i> l <sup>q</sup> </i> penalty term

0 references

Bayesian computation: a summary of the current state, and samples backwards and forwards

0 references

Full-wave invisibility of active devices at all frequencies

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On Bayesian estimation and proximity operators

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Bayesian inverse problems with partial observations

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Stable architectures for deep neural networks

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Learning regularization functionals a supervised training approach

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Numerical methods for the design of large-scale nonlinear discrete ill-posed inverse problems

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Dynamic linear inverse problems with moderate movements of the object: ill-posedness and regularization

0 references

Regularization by discretization in Banach spaces

0 references

0 references

Regularization methods for large-scale problems

0 references

Analysis of Discrete Ill-Posed Problems by Means of the L-Curve

0 references

Convergence Analysis of Primal-Dual Algorithms for a Saddle-Point Problem: From Contraction Perspective

0 references

Maximum<i>a posteriori</i>probability estimates in infinite-dimensional Bayesian inverse problems

0 references

Deep Learning: An Introduction for Applied Mathematicians

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Optimal selection of the regularization function in a weighted total variation model. I: Modelling and theory

0 references

Bilevel optimization for calibrating point spread functions in blind deconvolution

0 references

Elliptic Mathematical Programs with Equilibrium Constraints in Function Space: Optimality Conditions and Numerical Realization

0 references

Optimal selection of the regularization function in a weighted total variation model. II: Algorithm, its analysis and numerical tests

0 references

On the degree of ill-posedness for nonlinear problems

0 references

A convergence rates result for Tikhonov regularization in Banach spaces with non-smooth operators

0 references

On the degree of ill-posedness for linear problems with noncompact operators

0 references

Characterizations of Variational Source Conditions, Converse Results, and Maxisets of Spectral Regularization Methods

0 references

Inverse problems with Poisson data: statistical regularization theory, applications and algorithms

0 references

Fourier integral operators. I

0 references

Multilayer feedforward networks are universal approximators

0 references

Artificial intelligence as structural estimation: Deep Blue, Bonanza, and AlphaGo

0 references

0 references

An analysis of electrical impedance tomography with applications to Tikhonov regularization

0 references

Sparsity regularization for parameter identification problems

0 references

Deep Convolutional Neural Network for Inverse Problems in Imaging

0 references

A note on “improper” problems in partial differential equations

0 references

Numerical solution of the equation of heat conduction for preceding times

0 references

0 references

Continuous dependence on data for solutions of partial differential equations with a prescribed bound

0 references

Statistical and computational inverse problems.

0 references

Statistical inverse problems: discretization, model reduction and inverse crimes

0 references

0 references

Adaptive discretizations for the choice of a Tikhonov regularization parameter in nonlinear inverse problems

0 references

Iterative regularization methods for nonlinear ill-posed problems

0 references

Posterior consistency and convergence rates for Bayesian inversion with hypoelliptic operators

0 references

SwitchNet: A Neural Network Model for Forward and Inverse Scattering Problems

0 references

Solving parametric PDE problems with artificial neural networks

0 references

Optimized first-order methods for smooth convex minimization

0 references

Convergence analysis of minimization-based noise level-free parameter choice rules for linear ill-posed problems

0 references

An introduction to the mathematical theory of inverse problems

0 references

Mathematical models for magnetic particle imaging

0 references

Bayes procedures for adaptive inference in inverse problems for the white noise model

0 references

Bayesian inverse problems with Gaussian priors

0 references

Bayesian Recovery of the Initial Condition for the Heat Equation

0 references

Iterative Joint Image Demosaicking and Denoising Using a Residual Denoising Network

0 references

Sparsity-promoting Bayesian inversion

0 references

Microlocal Analysis in Tomography

0 references

0 references

A Bilevel Optimization Approach for Parameter Learning in Variational Models

0 references

0 references

Resolution of the wavefront set using continuous shearlets

0 references

Shearlets. Multiscale analysis for multivariate data.

0 references

Discretization-invariant Bayesian inversion and Besov space priors

0 references

Asymmetric forward-backward-adjoint splitting for solving monotone inclusions involving three operators

0 references

0 references

Asymptotic methods in statistical decision theory

0 references

Linear inverse problems for generalised random variables

0 references

NETT: solving inverse problems with deep neural networks

0 references

Statistical decision theory. Estimation, testing, and selection.

0 references

0 references

Approximate inverse for linear and some nonlinear problems

0 references

Feature reconstruction in inverse problems

0 references

A mollifier method for linear operator equations of the first kind

0 references

Regularized Total Least Squares: Computational Aspects and Error Bounds

0 references

Deep Learning for Trivial Inverse Problems

0 references

Sparse Modeling for Image and Vision Processing

0 references

0 references

0 references

Group Invariant Scattering

0 references

Matching pursuits with time-frequency dictionaries

0 references

Linear estimators and measurable linear transformations on a Hilbert space

0 references

Cauchy difference priors for edge-preserving Bayesian inversion

0 references

Overview of total least-squares methods

0 references

Biomedical Image Reconstruction: From the Foundations to Deep Neural Networks

0 references

Least Squares Methods for Ill-Posed Problems with a Prescribed Bound

0 references

Understanding the Hastings Algorithm

0 references

Efficient nonparametric Bayesian inference for \(X\)-ray transforms

0 references

0 references

Linear and Nonlinear Inverse Problems with Practical Applications

0 references

Optimal approximations by piecewise smooth functions and associated variational problems

0 references

Regularisierung schlecht gestellter Probleme durch Projektionsverfahren

0 references

The Mathematics of Computerized Tomography

0 references

Mathematical Methods in Image Reconstruction

0 references

Slice sampling. (With discussions and rejoinder)

0 references

CoSaMP: Iterative signal recovery from incomplete and inaccurate samples

0 references

Uniform uncertainty principle and signal recovery via regularized orthogonal matching pursuit

0 references

Introductory lectures on convex optimization. A basic course.

0 references

Convergence results for the Bayesian inversion theory

0 references

Nonparametric Bayesian posterior contraction rates for discretely observed scalar diffusions

0 references

Convergence Rates for Penalized Least Squares Estimators in PDE Constrained Regression Problems

0 references

0 references

A Generalized Mathematical Program with Equilibrium Constraints

0 references

Fast and Reliable Parameter Estimation from Nonlinear Observations

0 references

0 references

Working Locally Thinking Globally: Theoretical Guarantees for Convolutional Sparse Coding

0 references

Non-local regularization of inverse problems

0 references

A Technique for the Numerical Solution of Certain Integral Equations of the First Kind

0 references

Fast Approximation of Algebraic Reconstruction Methods for Tomography

0 references

On the regularization of projection methods for solving ill-posed problems

0 references

Singularities of the X-Ray Transform and Limited Data Tomography in $\mathbb{R}^2 $ and $\mathbb{R}^3 $

0 references

Local Tomography in Electron Microscopy

0 references

Hidden physics models: machine learning of nonlinear partial differential equations

0 references

Bayesian inverse problems with non-conjugate priors

0 references

Scalable Bayesian Uncertainty Quantification in Imaging Inverse Problems via Convex Optimization

0 references

Structural Properties of Solutions to Total Variation Regularization Problems

0 references

A Stochastic Approximation Method

0 references

0 references

Variational Analysis

0 references

The Little Engine that Could: Regularization by Denoising (RED)

0 references

Nonlinear total variation based noise removal algorithms

0 references

0 references

Theory of statistics

0 references

A modified Landweber iteration for solving parameter estimation problems

0 references

Variational methods in imaging

0 references

Efficient algorithms for the regularization of dynamic inverse problems: I. Theory

0 references

The method of approximate inverse: Theory and applications

0 references

Dynamic inverse problems: modelling—regularization—numerics

0 references

Regularization methods in Banach spaces.

0 references

Deep null space learning for inverse problems: convergence analysis and rates

0 references

On Bayes procedures

0 references

Well posedness and convergence of some regularisation methods for non-linear ill posed problems

0 references

Understanding Machine Learning

0 references

DGM: a deep learning algorithm for solving partial differential equations

0 references

Inverse problems: A Bayesian perspective

0 references

Posterior consistency for Gaussian process approximations of Bayesian posterior distributions

0 references

Multi-Layer Convolutional Sparse Modeling: Pursuit and Dictionary Learning

0 references

Empirical Bayes scaling of Gaussian priors in the white noise model

0 references

Inverse Problem Theory and Methods for Model Parameter Estimation

0 references

Regularization of linear ill-posed problems with noisy right hand side and noisy operator

0 references

Smooth strongly convex interpolation and exact worst-case performance of first-order methods

0 references

0 references

0 references

0 references

Signal Recovery From Random Measurements Via Orthogonal Matching Pursuit

0 references

The inverse problem for the local geodesic ray transform

0 references

Fractional Splines and Wavelets

0 references

Learning optimal spatially-dependent regularization parameters in total variation image denoising

0 references

A Statistical Model for Positron Emission Tomography

0 references

Optimal Transport

0 references

Deep Gaussian mixture models

0 references

Frequentist Consistency of Variational Bayes

0 references

0 references

Deep Convolutional Framelets: A General Deep Learning Framework for Inverse Problems

0 references

Sparsity-Cognizant Total Least-Squares for Perturbed Compressive Sampling

0 references

full work available at URL

https://doi.org/10.1017/s0962492919000059

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