| A Sparse ℋ-Matrix Arithmetic. W Hackbusch, BN Khoromskij Computing 64 (1), 21-47, 2000 | 1748* | 2000 |
| O(dlog N)-Quantics Approximation of N-d Tensors in High-Dimensional Numerical Modeling BN Khoromskij Constructive Approximation 34, 257-280, 2011 | 334 | 2011 |
| Tensors-structured numerical methods in scientific computing: Survey on recent advances BN Khoromskij Chemometrics and Intelligent Laboratory Systems 110 (1), 1-19, 2012 | 247 | 2012 |
| Tensor-structured Galerkin approximation of parametric and stochastic elliptic PDEs BN Khoromskij, C Schwab SIAM journal on scientific computing 33 (1), 364-385, 2011 | 222 | 2011 |
| Hierarchical Kronecker Tensor Product Approximations W Hackbusch, BN Khoromskij, EE Tyrtyshnikov J. Numer. Math. 13 (2), 119-156, 2005 | 168 | 2005 |
| Low-rank Kronecker-product approximation to multi-dimensional nonlocal operators. Part I. Separable approximation of multi-variate functions W Hackbusch, BN Khoromskij Computing 76, 177-202, 2006 | 161 | 2006 |
| Low-rank explicit QTT representation of the Laplace operator and its inverse VA Kazeev, BN Khoromskij SIAM journal on matrix analysis and applications 33 (3), 742-758, 2012 | 157 | 2012 |
| Fast solution of parabolic problems in the tensor train/quantized tensor train format with initial application to the Fokker--Planck equation SV Dolgov, BN Khoromskij, IV Oseledets SIAM Journal on Scientific Computing 34 (6), A3016-A3038, 2012 | 152* | 2012 |
| Multigrid accelerated tensor approximation of function related multidimensional arrays BN Khoromskij, V Khoromskaia SIAM Journal on Scientific Computing 31 (4), 3002-3026, 2009 | 147 | 2009 |
| Hierarchical matrices based on a weak admissibility criterion W Hackbusch, BN Khoromskij, R Kriemann Computing 73, 207-243, 2004 | 146 | 2004 |
| Approximate iterations for structured matrices W Hackbusch, BN Khoromskij, EE Tyrtyshnikov Numerische Mathematik 109 (3), 365-383, 2008 | 136 | 2008 |
| Solution of large scale algebraic matrix Riccati equations by use of hierarchical matrices L Grasedyck, W Hackbusch, BN Khoromskij Computing 70, 121-165, 2003 | 131 | 2003 |
| A sparse H-matrix arithmetic: general complexity estimates W Hackbusch, BN Khoromskij Journal of computational and applied mathematics 125 (1-2), 479-501, 2000 | 127 | 2000 |
| Computation of extreme eigenvalues in higher dimensions using block tensor train format SV Dolgov, BN Khoromskij, IV Oseledets, DV Savostyanov Computer Physics Communications 185 (4), 1207-1216, 2014 | 124 | 2014 |
| Low rank Tucker-type tensor approximation to classical potentials B Khoromskij, V Khoromskaia Open Mathematics 5 (3), 523-550, 2007 | 124 | 2007 |
| Application of hierarchical matrices for computing the Karhunen–Loeve expansion BN Khoromskij, A Litvinenko, HG Matthies Computing 84 (1), 49-67, 2009 | 118 | 2009 |
| -Matrix approximation for the operator exponential with applications IP Gavrilyuk, W Hackbusch, BN Khoromskij Numerische Mathematik 92 (1), 83-111, 2002 | 114 | 2002 |
| Numerical solution of the Hartree–Fock equation in multilevel tensor-structured format BN Khoromskij, V Khoromskaia, HJ Flad SIAM journal on scientific computing 33 (1), 45-65, 2011 | 112 | 2011 |
| Tensor-product approximation to operators and functions in high dimensions W Hackbusch, BN Khoromskij Journal of Complexity 23 (4-6), 697-714, 2007 | 112 | 2007 |
| Simultaneous state‐time approximation of the chemical master equation using tensor product formats S Dolgov, B Khoromskij Numerical Linear Algebra with Applications 22 (2), 197-219, 2015 | 110* | 2015 |
Venera KhoromskaiaSenior Scientist, Max-Planck Institute for Mathematics in the Sciences在 mis.mpg.de 的电子邮件经过验证
