2 citations · 3 across the 3 of their papers we have counts for
3 papers
math.NA2026
Low-rank eigenvalue solvers for block-sparse matrix product states
Markus Bachmayr, Sebastian Krämer, Max Pfeffer
We consider an iterative eigensolver for Schrödinger equations that constructs low-rank approximations of eigenfunctions with accuracy-adapted ranks, with particular focus on fermi…
math.NA2021★ 2 cited
Asymptotic Log-Det Sum-of-Ranks Minimization via Tensor (Alternating) Iteratively Reweighted Least Squares
Sebastian Krämer
Affine sum-of-ranks minimization (ASRM) generalizes the affine rank minimization (ARM) problem from matrices to tensors. Here, the interest lies in the ranks of a family $\mathcal{…
math.OC2021★ 1 cited
Asymptotic Log-Det Rank Minimization via (Alternating) Iteratively Reweighted Least Squares
Sebastian Krämer
The affine rank minimization (ARM) problem is well known for both its applications and the fact that it is NP-hard. One of the most successful approaches, yet arguably underreprese…