Results 221 to 230 of about 165,068 (255)

Quantum Information Theory on Sparse Wave Functions and Applications for Quantum Chemistry. [PDF]

J Phys Chem A
Materia D, Ratini L, Guidoni L.
europepmc   +1 more source

Improving polygenic score prediction for underrepresented groups through transfer learning. [PDF]

Nat Commun
Wu H, Pérez-Rodríguez P, Boehnke M, Cui Y, Liang X, Vazquez AI, de Los Campos G.   +6 more
europepmc   +1 more source

Faster quantum subroutine for matrix chain multiplication via Chebyshev approximation. [PDF]

Sci Rep
Li X, Zheng PL, Pan C, Wang F, Cui C, Lu X.   +5 more
europepmc   +1 more source

A deep dictionary clustering approach for unsupervised image retrieval using convolutional sparse coding. [PDF]

Sci Rep
Sucharitha G, Vikas B, Reddy PVB, Suneel S, Divya N, Osman O, Rasheed J.   +6 more
europepmc   +1 more source

A Multidimensional Matrix Completion Method for 2-D DOA Estimation with L-Shaped Array. [PDF]

Sensors (Basel)
Zhang H, Shi J, Li Z, Shi S.
europepmc   +1 more source

Computational Methods for General Sparse Matrices

, 1991
Zahari Zlatev
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Computational methods for sparse matrices

Computer Physics Communications, 1980
Abstract This paper is a survey of methods currently available for processing sparse matrices in a digital computer; specifically in the solution of linear algebraic equations and the eigenproblem.
C.M.M. Nex
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Generalizations of Davidson’s Method for Computing Eigenvalues of Sparse Symmetric Matrices

SIAM Journal on Scientific and Statistical Computing, 1986
The method of \textit{E. R. Davidson} [J. Comput. Phys. 17, 87-94 (1975; Zbl 0293.65022)] for computing a few eigenpairs of large sparse symmetric matrices is analyzed as a method for using diagonal preconditioning (i.e. using an approximate inverse).
Morgan, Ronald B., Scott, David S.
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A hybrid method for the solution of sparse power system matrices on vector computers

38th Midwest Symposium on Circuits and Systems. Proceedings, 2002
This paper describes a methodology for solving a linear system of equations on vector computer. The methodology combines direct and inverse factors. The decomposition and implementation of the direct solution in a CRAY Y-MPZE/232, and the performance results are discussed.
A. Padilha, A.R. Basso
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A Golub--Kahan Davidson Method for Accurately Computing a Few Singular Triplets of Large Sparse Matrices

SIAM Journal on Scientific Computing, 2019
Summary: Obtaining high accuracy singular triplets for large sparse matrices is a significant challenge, especially when searching for the smallest triplets. Due to the difficulty and size of these problems, efficient methods must function iteratively, with preconditioners, and under strict memory constraints. In this research, we present a Golub-Kahan
Goldenberg, Steven, Stathopoulos, Andreas, Romero, Eloy   +2 more
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