MCMC Algorithms for Computational UQ of Nonnegativity Constrained Linear Inverse Problems | Zendy

Johnathan M. Bardsley | Zendy; Per Christian Hansen | Zendy

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MCMC Algorithms for Computational UQ of Nonnegativity Constrained Linear Inverse Problems

Author(s) -

Johnathan M. Bardsley,

Per Christian Hansen

Publication year - 2020

Publication title -

siam journal on scientific computing

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.674

H-Index - 147

eISSN - 1095-7197

pISSN - 1064-8275

DOI - 10.1137/18m1234588

Subject(s) - mathematics , markov chain monte carlo , mathematical optimization , inverse problem , algorithm , deblurring , gaussian , bayesian probability , computer science , image restoration , image processing , image (mathematics) , artificial intelligence , mathematical analysis , physics , quantum mechanics , statistics

In many inverse problems, a nonnegativity constraint is natural. Moreover, in some cases, we expect the vector of unknown parameters to have zero components. When a Bayesian approach is taken, this...

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