Laplacian matrices of graphs arise in large-scale computational applications such as
semisupervised machine learning; spectral clustering of images, genetic data, and web …

Computational fluid dynamics (CFD) has its origins in fluid mechanics and mathematics but
finds applications in diverse fields of engineering and science. The rapid spread of CFD …

In a recent paper, the author examined a correlation affinity measure for selecting the coarse
degrees of freedom (CDOFs) or coarse nodes (C nodes) in systems of elliptic partial …

A new algorithm based on algebraic multigrid is presented for computing the rank-R
canonical decomposition of a tensor for small R. Standard alternating least squares (ALS) is …

A new adaptive algebraic multigrid scheme is developed for the solution of Markov chains,
where the hierarchy of operators is adapted on-the-fly in a setup process that is interlaced …

Tensor structured Markov chains are part of stochastic models of many practical
applications, eg, in the description of complex production or telephone networks. The most …

We develop an algebraic multigrid method for solving the non-Hermitian Wilson
discretization of the two-dimensional Dirac equation. The proposed approach uses a …

We propose nonsymmetric lean algebraic multigrid (NS‐LAMG), a new algebraic multigrid
algorithm for directed graph Laplacian systems that combines ideas from undirected graph …

A self-learning algebraic multigrid method for dominant and minimal singular triplets and
eigenpairs is described. The method consists of two multilevel phases. In the first …

The paper introduces a new adaptive method for solving the one-dimensional Helmholtz
equation. It is implemented in algebraic multigrid framework and combines techniques from …