Inverse problems in blood flow modeling: A review
Sign Up to like & getrecommendations! Published in 2022 at "International Journal for Numerical Methods in Biomedical Engineering"
DOI: 10.1002/cnm.3613
Abstract: Mathematical and computational modeling of the cardiovascular system is increasingly providing non‐invasive alternatives to traditional invasive clinical procedures. Moreover, it has the potential for generating additional diagnostic markers. In blood flow computations, the personalization of… read more here.
Keywords: inverse problems; inverse; review; problems blood ... See more keywords
Inverse Problems in Systems Biology: A Critical Review.
Sign Up to like & getrecommendations! Published in 2018 at "Methods in molecular biology"
DOI: 10.1007/978-1-4939-7456-6_6
Abstract: Systems Biology may be assimilated to a symbiotic cyclic interplaying between the forward and inverse problems. Computational models need to be continuously refined through experiments and in turn they help us to make limited experimental… read more here.
Keywords: biology; inverse problems; problems systems; critical review ... See more keywords
Partial Inverse Problems for Dirac Operators on Star Graphs
Sign Up to like & getrecommendations! Published in 2020 at "Mediterranean Journal of Mathematics"
DOI: 10.1007/s00009-020-01620-5
Abstract: Partial inverse problems for Dirac operators on star graphs are studied. We consider Dirac operators on the graphs, and prove that the potential on one edge is uniquely determined by part of its spectra and… read more here.
Keywords: dirac operators; problems dirac; star graphs; inverse problems ... See more keywords
Solving Bayesian inverse problems from the perspective of deep generative networks
Sign Up to like & getrecommendations! Published in 2019 at "Computational Mechanics"
DOI: 10.1007/s00466-019-01739-7
Abstract: Deep generative networks have achieved great success in high dimensional density approximation, especially for applications in natural images and language. In this paper, we investigate their approximation capability in capturing the posterior distribution in Bayesian… read more here.
Keywords: bayesian inverse; deep generative; inverse problems; solving bayesian ... See more keywords
Off-the-grid regularisation for Poisson inverse problems
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DOI: 10.1007/s10589-025-00688-7
Abstract: Off-the-grid regularisation has been extensively employed over the last decade in the context of ill-posed inverse problems formulated in the continuous setting of the space of Radon measures M(Ω)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs}… read more here.
Keywords: inverse problems; poisson; grid regularisation; document ... See more keywords
A Numerical Method for the Solution of Two Inverse Problems in the Mathematical Model of Redox Sorption
Sign Up to like & getrecommendations! Published in 2020 at "Computational Mathematics and Modeling"
DOI: 10.1007/s10598-020-09478-8
Abstract: For a mathematical model with internal-diffusion kinetics and an oxidation-reduction reaction, we consider two inverse problems of determining the sorption isotherm or the redox reaction rate constant from the output dynamic curve. A numerical method… read more here.
Keywords: numerical method; method solution; inverse problems; inverse ... See more keywords
Big in Japan: Regularizing Networks for Solving Inverse Problems
Sign Up to like & getrecommendations! Published in 2019 at "Journal of Mathematical Imaging and Vision"
DOI: 10.1007/s10851-019-00911-1
Abstract: Deep learning and (deep) neural networks are emerging tools to address inverse problems and image reconstruction tasks. Despite outstanding performance, the mathematical analysis for solving inverse problems by neural networks is mostly missing. In this… read more here.
Keywords: mathbf alpha; inverse problems; solving inverse; regularization ... See more keywords
Ray Expansions and Identities for Second Order Equations. Applications to Inverse Problems
Sign Up to like & getrecommendations! Published in 2018 at "Journal of Mathematical Sciences"
DOI: 10.1007/s10958-018-3809-x
Abstract: We develop a new method for studying inverse problems of mathematical physics by using systems of equations of ray expansion of solutions to parabolic and hyperbolic equations with variable coefficients. read more here.
Keywords: second order; expansions identities; order equations; ray expansions ... See more keywords
Unbiased parameter estimation for bayesian inverse problems
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DOI: 10.1007/s11222-025-10768-7
Abstract: In this paper we consider the estimation of unknown parameters in Bayesian inverse problems. In most cases of practical interest, there are several barriers to performing such estimation, This includes a numerical approximation of a… read more here.
Keywords: methodology; inverse problems; bayesian inverse; parameter estimation ... See more keywords
Inverse problems associated with subsequence sums in Cp ⊕ Cp
Sign Up to like & getrecommendations! Published in 2020 at "Frontiers of Mathematics in China"
DOI: 10.1007/s11464-020-0869-2
Abstract: Let G be a finite abelian group and S be a sequence with elements of G. We say that S is a regular sequence over G if ∣SH∣ ⩽ ∣H∣ − 1 holds for every… read more here.
Keywords: problems associated; subsequence sums; subsequence; inverse problems ... See more keywords
An introduction of Markov chain Monte Carlo method to geochemical inverse problems: Reading melting parameters from REE abundances in abyssal peridotites
Sign Up to like & getrecommendations! Published in 2017 at "Geochimica et Cosmochimica Acta"
DOI: 10.1016/j.gca.2016.12.040
Abstract: Abstract Markov chain Monte Carlo (MCMC) simulation is a powerful statistical method in solving inverse problems that arise from a wide range of applications. In Earth sciences applications of MCMC simulations are primarily in the… read more here.
Keywords: chain; method; markov chain; inverse problems ... See more keywords