HyBR swMATH ID: 29132 Software Authors: Description: Hybrid Bidiagonalization Regularization (HyBR). Hybrid regularization methods have been proposed as effective approaches for solving large-scale ill-posed inverse problems. These methods restrict the solution to lie in a Krylov subspace, but they are hindered by semi-convergence behavior, in that the quality of the solution first increases and then decreases. Hybrid methods apply a standard regularization technique, such as Tikhonov regularization, to the projected problem at each iteration. Thus, regularization in hybrid methods is achieved both by Krylov filtering and by appropriate choice of a regularization parameter at each iteration. Homepage: http://www.math.vt.edu/people/jmchung/hybr.html Source Code: https://github.com/juliannechung/genHyBR Dependencies: Matlab Related Software: Regularization tools; IR Tools; AIR tools; GKB-FP; RestoreTools; CRAIG; LSQR; ForWaRD; LSMR; NETT; UTV; Matlab Cited in: 8 Documents Standard Articles 1 Publication describing the Software, including 1 Publication in zbMATH Year Generalized hybrid iterative methods for large-scale Bayesian inverse problems. Zbl 1422.65065Chung, Julianne; Saibaba, Arvind K. 2017 all top 5 Cited by 13 Authors 5 Chung, Julianne M. 3 Jiang, Jiahua 2 de Sturler, Eric 2 Saibaba, Arvind Krishna 1 Cho, Taewon 1 Gazzola, Silvia 1 Hansen, Per Christian 1 Jia, Zhongxiao 1 Nagy, James Gerard 1 Reichel, Lothar 1 Ugwu, Ugochukwu O. 1 Westman, Erik 1 Yang, Yanfei Cited in 5 Serials 3 SIAM Journal on Scientific Computing 2 Inverse Problems 1 Journal of Computational and Applied Mathematics 1 Applied Numerical Mathematics 1 Numerical Algorithms Cited in 5 Fields 8 Numerical analysis (65-XX) 3 Linear and multilinear algebra; matrix theory (15-XX) 1 Statistics (62-XX) 1 Computer science (68-XX) 1 Biology and other natural sciences (92-XX) Citations by Year