The following pages link to Tensor-Train Decomposition (Q126157):
Displaying 50 items.
- Nonnegative tensor train factorization with DMRG technique (Q2304589) (← links)
- Variational Monte Carlo -- bridging concepts of machine learning and high-dimensional partial differential equations (Q2305540) (← links)
- Analysis of parametric models. Linear methods and approximations (Q2305542) (← links)
- Computing images of polynomial maps (Q2305553) (← links)
- Tensor neural network models for tensor singular value decompositions (Q2307707) (← links)
- Tensor train approximation of moment equations for elliptic equations with lognormal coefficient (Q2308598) (← links)
- Low rank tensor methods in Galerkin-based isogeometric analysis (Q2309006) (← links)
- Unfoldings and the rank-one approximation of the tensor (Q2309259) (← links)
- Gradient-based optimization for regression in the functional tensor-train format (Q2312177) (← links)
- Tensor trains approximation estimates in the Chebyshev norm (Q2313430) (← links)
- Editorial. Tensor numerical methods: actual theory and recent applications (Q2324346) (← links)
- A tensor decomposition algorithm for large ODEs with conservation laws (Q2324349) (← links)
- Non-intrusive tensor reconstruction for high-dimensional random PDEs (Q2324350) (← links)
- Quasi-optimal rank-structured approximation to multidimensional parabolic problems by Cayley transform and Chebyshev interpolation (Q2324351) (← links)
- Projection methods for dynamical low-rank approximation of high-dimensional problems (Q2324352) (← links)
- Tensor train spectral method for learning of hidden Markov models (HMM) (Q2324354) (← links)
- Tucker tensor analysis of Matérn functions in spatial statistics (Q2324355) (← links)
- Approximate solution of linear systems with Laplace-like operators via cross approximation in the frequency domain (Q2324358) (← links)
- Finite state projection for approximating the stationary solution to the chemical master equation using reaction rate equations (Q2328496) (← links)
- Tensor-train format solution with preconditioned iterative method for high dimensional time-dependent space-fractional diffusion equations with error analysis (Q2330680) (← links)
- Low-rank tensor completion based on log-det rank approximation and matrix factorization (Q2330690) (← links)
- Tensor representation of non-linear models using cross approximations (Q2333682) (← links)
- Low-rank tensor completion using matrix factorization based on tensor train rank and total variation (Q2333730) (← links)
- Stable als approximation in the TT-format for rank-adaptive tensor completion (Q2334620) (← links)
- Optimization on the hierarchical Tucker manifold - applications to tensor completion (Q2350002) (← links)
- Adaptive stochastic Galerkin FEM with hierarchical tensor representations (Q2364893) (← links)
- A low-rank approach to the computation of path integrals (Q2374948) (← links)
- Numerical methods for high-dimensional probability density function equations (Q2374964) (← links)
- Solving the master equation without kinetic Monte Carlo: tensor train approximations for a CO oxidation model (Q2375145) (← links)
- Tensor train versus Monte Carlo for the multicomponent Smoluchowski coagulation equation (Q2375224) (← links)
- Low rank tensor recovery via iterative hard thresholding (Q2400255) (← links)
- QTT-finite-element approximation for multiscale problems. I: Model problems in one dimension (Q2400487) (← links)
- Iterative methods based on soft thresholding of hierarchical tensors (Q2407677) (← links)
- Low-rank solvers for unsteady Stokes-Brinkman optimal control problem with random data (Q2417696) (← links)
- Approximation rates for the hierarchical tensor format in periodic Sobolev spaces (Q2442808) (← links)
- An equi-directional generalization of adaptive cross approximation for higher-order tensors (Q2448363) (← links)
- A projector-splitting integrator for dynamical low-rank approximation (Q2450891) (← links)
- Superfast solution of linear convolutional Volterra equations using QTT approximation (Q2511217) (← links)
- Randomized algorithms for the approximations of Tucker and the tensor train decompositions (Q2631991) (← links)
- Robust low transformed multi-rank tensor methods for image alignment (Q2660687) (← links)
- Global and local optimization in identification of parabolic systems (Q2660798) (← links)
- MERACLE: constructive layer-wise conversion of a tensor train into a MERA (Q2667352) (← links)
- Tensorized low-rank circulant preconditioners for multilevel Toeplitz linear systems from high-dimensional fractional Riesz equations (Q2667987) (← links)
- Tensor-Krylov method for computing eigenvalues of parameter-dependent matrices (Q2668025) (← links)
- Born machine model based on matrix product state quantum circuit (Q2669398) (← links)
- Fast nonnegative tensor factorizations with tensor train model (Q2674997) (← links)
- A Lanczos-type procedure for tensors (Q2679666) (← links)
- Analysis of tensor approximation schemes for continuous functions (Q2684464) (← links)
- Low-rank nonnegative tensor approximation via alternating projections and sketching (Q2685220) (← links)
- Tensor approximation of the self-diffusion matrix of tagged particle processes (Q2689616) (← links)
