References in zbMATH (referenced in 53 articles )

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  1. Al Daas, Hussam; Ballard, Grey; Benner, Peter: Parallel algorithms for tensor train arithmetic (2022)
  2. Leveque, Santolo; Pearson, John W.: Parameter-robust preconditioning for Oseen iteration applied to stationary and instationary Navier-Stokes control (2022)
  3. Manzini, Gianmarco; Skau, Erik; Truong, Duc P.; Vangara, Raviteja: Nonnegative tensor-train low-rank approximations of the Smoluchowski coagulation equation (2022)
  4. Chen, Can; Surana, Amit; Bloch, Anthony M.; Rajapakse, Indika: Multilinear control systems theory (2021)
  5. Dektor, Alec; Venturi, Daniele: Dynamic tensor approximation of high-dimensional nonlinear PDEs (2021)
  6. Liang, Maolin; Zheng, Bing; Zheng, Yutao; Zhao, Ruijuan: A two-step accelerated Levenberg-Marquardt method for solving multilinear systems in tensor-train format (2021)
  7. Markeeva, L.; Tsybulin, I.; Oseledets, I.: QTT-isogeometric solver in two dimensions (2021)
  8. Rakhuba, M.: Robust alternating direction implicit solver in quantized tensor formats for a three-dimensional elliptic PDE (2021)
  9. Bünger, Alexandra; Dolgov, Sergey; Stoll, Martin: A low-rank tensor method for PDE-constrained optimization with isogeometric analysis (2020)
  10. Dolgov, Sergey; Anaya-Izquierdo, Karim; Fox, Colin; Scheichl, Robert: Approximation and sampling of multivariate probability distributions in the tensor train decomposition (2020)
  11. Elman, Howard C.; Su, Tengfei: A low-rank solver for the stochastic unsteady Navier-Stokes problem (2020)
  12. Espig, Mike; Hackbusch, Wolfgang; Litvinenko, Alexander; Matthies, Hermann G.; Zander, Elmar: Iterative algorithms for the post-processing of high-dimensional data (2020)
  13. Novikov, Alexander; Izmailov, Pavel; Khrulkov, Valentin; Figurnov, Michael; Oseledets, Ivan: Tensor train decomposition on TensorFlow (T3F) (2020)
  14. Shcherbakova, Elena; Tyrtyshnikov, Eugene: Nonnegative tensor train factorizations and some applications (2020)
  15. Che, Maolin; Wei, Yimin: Randomized algorithms for the approximations of Tucker and the tensor train decompositions (2019)
  16. Dolgov, Sergey; Scheichl, Robert: A hybrid alternating least squares-TT-cross algorithm for parametric PDEs (2019)
  17. Liang, Maolin; Zheng, Bing; Zhao, Ruijuan: Alternating iterative methods for solving tensor equations with applications (2019)
  18. Shcherbakova, E. M.: Nonnegative tensor train factorization with DMRG technique (2019)
  19. Tyrtyshnikov, E. E.; Shcherbakova, E. M.: Methods for nonnegative matrix factorization based on low-rank cross approximations (2019)
  20. Vervliet, Nico; Debals, Otto; De Lathauwer, Lieven: Exploiting efficient representations in large-scale tensor decompositions (2019)

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