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The photoacoustic tomography (PAT) is a hybrid modality that combines the optics and acoustics to obtain high resolution and high contrast imaging of heterogeneous media. In this work, our objective is to study the inverse problem in the…

Numerical Analysis · Mathematics 2021-05-26 Hongkai Zhao , Yimin Zhong

Algorithms for the numerical evaluation of the incomplete gamma function ratios $P(a,x)=\gamma(a,x)/\Gamma(a)$ and $Q(a,x)=\Gamma(a,x)/\Gamma(a)$ are described for positive values of $a$ and $x$. Also, inversion methods are given for…

Classical Analysis and ODEs · Mathematics 2013-06-10 Amparo Gil , Javier Segura , Nico M. Temme

In this paper, a nonsmooth semilinear parabolic partial differential equation (PDE) is considered. For a reduced basis (RB) approach, a space-time formulation is used to develop a certified a-posteriori error estimator. This error estimator…

Numerical Analysis · Mathematics 2022-12-29 Marco Bernreuther , Stefan Volkwein

A variational model for learning convolutional image atoms from corrupted and/or incomplete data is introduced and analyzed both in function space and numerically. Building on lifting and relaxation strategies, the proposed approach is…

Optimization and Control · Mathematics 2018-12-10 Antonin Chambolle , Martin Holler Thomas Pock

Many known Radon-type transforms of symmetric (radial or zonal) functions are represented by one-dimensional Riemann-Liouville fractional integrals or their modifications. The present article contains new examples of such transforms in the…

Functional Analysis · Mathematics 2024-12-31 Boris Rubin

A ring electrode of an RRDE setup is often used to detect a redox active specie produced at the disk electrode. It is especially useful when some side processes occur at the disk (e.g. passivation film growth) along with the main…

Applied Physics · Physics 2018-01-10 Artem V. Sergeev , Daniil M. Itkis , Alexander V. Chertovich

X-ray interaction with matter is an energy-dependent process that is contingent on the atomic structure of the constituent material elements. The most advanced models to capture this relationship currently rely on Monte Carlo (MC)…

Machine Learning · Computer Science 2023-07-11 Raziye Kubra Kumrular , Thomas Blumensath

Sliced optimal transport reduces optimal transport on multi-dimensional domains to transport on the line. More precisely, sliced optimal transport is the concatenation of the well-known Radon transform and the cumulative density transform,…

Numerical Analysis · Mathematics 2024-07-03 Michael Quellmalz , Robert Beinert , Gabriele Steidl

This work introduces a new approach for accelerating the numerical analysis of time-domain partial differential equations (PDEs) governing complex physical systems. The methodology is based on a combination of a classical reduced-order…

Machine Learning · Computer Science 2024-06-06 Victor Matray , Faisal Amlani , Frédéric Feyel , David Néron

One of the major challenges in the Bayesian solution of inverse problems governed by partial differential equations (PDEs) is the computational cost of repeatedly evaluating numerical PDE models, as required by Markov chain Monte Carlo…

Computation · Statistics 2016-05-03 Tiangang Cui , Youssef M. Marzouk , Karen E. Willcox

In this paper we consider the solution of monotone inverse problems using the particular example of a parameter identification problem for a semilinear parabolic PDE. For the regularized solution of this problem, we introduce a total…

Numerical Analysis · Mathematics 2025-02-26 Pankaj Gautam , Markus Grasmair

Inspired by the multiple-exposure fusion approach in computational photography, recently, several practitioners have explored the idea of high dynamic range (HDR) X-ray imaging and tomography. While establishing promising results, these…

Numerical Analysis · Mathematics 2024-04-10 Matthias Beckmann , Ayush Bhandari , Meira Iske

The approximate discrete Radon transform (ADRT) is a hierarchical multiscale approximation of the Radon transform. In this paper, we factor the ADRT into a product of linear transforms that resemble convolutions and derive an explicit…

Numerical Analysis · Mathematics 2026-01-08 Weilin Li , Karl Otness , Kui Ren , Donsub Rim

A general method for analytic inversion in integral geometry is proposed. All classical and some new reconstruction formulas of Radon-John type are obtained by this method. No harmonic analysis and PDE is used.

Differential Geometry · Mathematics 2015-06-03 Victor P. Palamodov

We present a novel, general-purpose method for deconvolving and denoising images from gridded radio interferometric visibilities using Bayesian inference based on a Gaussian process model. The method automatically takes into account…

Instrumentation and Methods for Astrophysics · Physics 2015-06-17 P. M. Sutter , Benjamin D. Wandelt , Jason D. McEwen , Emory F. Bunn , Ata Karakci , Andrei Korotkov , Peter Timbie , Gregory S. Tucker , Le Zhang

The aim of reduced rank regression is to connect multiple response variables to multiple predictors. This model is very popular, especially in biostatistics where multiple measurements on individuals can be re-used to predict multiple…

Methodology · Statistics 2022-06-20 The Tien Mai , Pierre Alquier

In nonlinear imaging problems whose forward model is described by a partial differential equation (PDE), the main computational bottleneck in solving the inverse problem is the need to solve many large-scale discretized PDEs at each step of…

Numerical Analysis · Mathematics 2016-03-08 Meghan O'Connell , Misha E. Kilmer , Eric de Sturler , Serkan Gugercin

X-ray resonant magnetic reflectivity (XRMR) is a powerful method to determine the optical, structural and magnetic depth profiles of a variety of thin films. Here, we investigate samples of different complexity all measured at the Pt L$_3$…

We consider the radiation transfer problem in the discrete-ordinate, plane-parallel approach. We introduce two benchmark problems with exact known solutions and show that for strongly non-homogeneous media the homogeneous layers…

Computational Physics · Physics 2007-05-23 M. -P. Zorzano , A. M. Mancho , L. Vazquez

Characterizing statistical properties of solutions of inverse problems is essential for decision making. Bayesian inversion offers a tractable framework for this purpose, but current approaches are computationally unfeasible for most…

Machine Learning · Statistics 2024-12-18 Jonas Adler , Ozan Öktem