References in zbMATH (referenced in 23 articles )

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  1. Dolgov, Sergey; Stoll, Martin: Low-rank solution to an optimization problem constrained by the Navier-Stokes equations (2017)
  2. Eigel, Martin; Pfeffer, Max; Schneider, Reinhold: Adaptive stochastic Galerkin FEM with hierarchical tensor representations (2017)
  3. Garreis, Sebastian; Ulbrich, Michael: Constrained optimization with low-rank tensors and applications to parametric problems with PDEs (2017)
  4. Hashemi, Behnam; Trefethen, Lloyd N.: Chebfun in three dimensions (2017)
  5. Benner, Peter; Onwunta, Akwum; Stoll, Martin: Block-diagonal preconditioning for optimal control problems constrained by PDEs with uncertain inputs (2016)
  6. Bolten, Matthias; Kahl, Karsten; Sokolović, Sonja: Multigrid methods for tensor structured Markov chains with low rank approximation (2016)
  7. Fan, H.-Y.; Zhang, L.; Chu, E.K.-w.; Wei, Y.: Q-less QR decomposition in inner product spaces (2016)
  8. Klus, Stefan; Schütte, Christof: Towards tensor-based methods for the numerical approximation of the Perron-Frobenius and Koopman operator (2016)
  9. Lee, Namgil; Cichocki, Andrzej: Regularized computation of approximate pseudoinverse of large matrices using low-rank tensor train decompositions (2016)
  10. Steinlechner, Michael: Riemannian optimization for high-dimensional tensor completion (2016)
  11. Dolgov, Sergey; Khoromskij, Boris: Simultaneous state-time approximation of the chemical master equation using tensor product formats. (2015)
  12. Dolgov, Sergey; Khoromskij, Boris N.; Litvinenko, Alexander; Matthies, Hermann G.: Polynomial chaos expansion of random coefficients and the solution of stochastic partial differential equations in the tensor train format (2015)
  13. Dolgov, Sergey V.; Tyrtyshnikov, Eugene E.: On evolution of solution times for the chemical master equation of the enzymatic futile cycle (2015)
  14. Lee, Namgil; Cichocki, Andrzej: Estimating a few extreme singular values and vectors for large-scale matrices in tensor train format (2015)
  15. Rakhuba, M.V.; Oseledets, I.V.: Fast multidimensional convolution in low-rank tensor formats via cross approximation (2015)
  16. Espig, Mike; Hackbusch, Wolfgang; Litvinenko, Alexander; Matthies, Hermann G.; Wähnert, Philipp: Efficient low-rank approximation of the stochastic Galerkin matrix in tensor formats (2014)
  17. Kressner, Daniel; Tobler, Christine: Algorithm 941: htucker -- a Matlab toolbox for tensors in hierarchical Tucker format (2014)
  18. Bebendorf, M.; Kühnemund, A.; Rjasanow, S.: An equi-directional generalization of adaptive cross approximation for higher-order tensors (2013)
  19. Grasedyck, Lars; Kressner, Daniel; Tobler, Christine: A literature survey of low-rank tensor approximation techniques (2013)
  20. Mach, T.: Computing inner eigenvalues of matrices in tensor train matrix format (2013)

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