Algorithm 941

51 citations recorded by the source corpus.

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Tensor Networks for Dimensionality Reduction and Large-scale Optimization: Part 1 Low-Rank Tensor Decompositions (2016, unknown): “For further control of the ranks, alternative tensor networks can be employed, such as: (1) the Honey-Comb Lattice (HCL) which uses 3rd-order cores, and (2) the Multi-scale Entanglement Renormalization Ansatz (MERA) which consist of both 3rd- and 4th-order core tensors (see Figure 27) [158, 201].”
Multilevel preconditioning and low‐rank tensor iteration for space–time simultaneous discretizations of parabolic PDEs (2015, methodology): “The numerical experiments below are based on the publicly available htucker toolbox [41, 42] in MATLAB which provides a representation of a tensor in H-Tucker format, as well as the operations described above.”
The geometry of algorithms using hierarchical tensors (2013, methodology): “truncate_ltr of [54].”
A preconditioned low‐rank CG method for parameter‐dependent Lyapunov matrix equations (2014, methodology): “In the following, we will only describe some key features of the hierarchical Tucker format and refer to [21, 22, 44] for more detailed descriptions.”