The following pages link to Tensor-Train Decomposition (Q126157):
Displaying 50 items.
- Tensor trains and moment conservation for multivariate aggregation in population balance modeling (Q1986174) (← links)
- A continuous analogue of the tensor-train decomposition (Q1987792) (← links)
- Multigrid methods combined with low-rank approximation for tensor-structured Markov chains (Q1990903) (← links)
- Direct tensor-product solution of one-dimensional elliptic equations with parameter-dependent coefficients (Q1997007) (← links)
- M-PCM-OFFD: an effective output statistics estimation method for systems of high dimensional uncertainties subject to low-order parameter interactions (Q1997513) (← links)
- Multigrid renormalization (Q2000454) (← links)
- Greedy low-rank approximation in Tucker format of solutions of tensor linear systems (Q2000621) (← links)
- Parallel tensor methods for high-dimensional linear PDEs (Q2002269) (← links)
- Finite volume approximation with ADI scheme and low-rank solver for high dimensional spatial distributed-order fractional diffusion equations (Q2019582) (← links)
- A two-stage surrogate model for neo-Hookean problems based on adaptive proper orthogonal decomposition and hierarchical tensor approximation (Q2020966) (← links)
- Tensor train rank minimization with nonlocal self-similarity for tensor completion (Q2037222) (← links)
- TT ranks of approximate tensorizations of some smooth functions (Q2038486) (← links)
- Structuring data with block term decomposition: decomposition of joint tensors and variational block term decomposition as a parametrized mixture distribution model (Q2038495) (← links)
- Prospects of tensor-based numerical modeling of the collective electrostatics in many-particle systems (Q2038503) (← links)
- Tensor-train numerical integration of multivariate functions with singularities (Q2046409) (← links)
- Using a partial differential equation with Google mobility data to predict COVID-19 in Arizona (Q2047760) (← links)
- Tensor theta norms and low rank recovery (Q2048814) (← links)
- Rank-adaptive tensor methods for high-dimensional nonlinear PDEs (Q2049083) (← links)
- Reshaped tensor nuclear norms for higher order tensor completion (Q2051256) (← links)
- The nonconvex tensor robust principal component analysis approximation model via the weighted \(\ell_p\)-norm regularization (Q2053328) (← links)
- Hybrid tensor decomposition in neural network compression (Q2057771) (← links)
- Tree-based tensor formats (Q2059130) (← links)
- Truncation of tensors in the hierarchical format (Q2059131) (← links)
- Low-rank tensor approximation of singularly perturbed boundary value problems in one dimension (Q2059731) (← links)
- Solving differential Riccati equations: a nonlinear space-time method using tensor trains (Q2061362) (← links)
- Faster tensor train decomposition for sparse data (Q2068649) (← links)
- A proximal point like method for solving tensor least-squares problems (Q2070322) (← links)
- Tensor approximation of cooperative games and their semivalues (Q2076973) (← links)
- Tensor-based computation of metastable and coherent sets (Q2077619) (← links)
- Uniform matrix product states from an algebraic geometer's point of view (Q2081910) (← links)
- Interval approach to solving parametric identification problems for dynamical systems (Q2082808) (← links)
- Adaptive force biasing algorithms: new convergence results and tensor approximations of the bias (Q2090609) (← links)
- An error bound for the time-sliced thawed Gaussian propagation method (Q2095800) (← links)
- Robust tensor recovery with nonconvex and nonsmooth regularization (Q2096313) (← links)
- Tensor train based isogeometric analysis for PDE approximation on parameter dependent geometries (Q2096827) (← links)
- Deep composition of tensor-trains using squared inverse Rosenblatt transports (Q2098237) (← links)
- Hot-SVD: higher order t-singular value decomposition for tensors based on tensor-tensor product (Q2099552) (← links)
- Committor functions via tensor networks (Q2099715) (← links)
- Color image and video restoration using tensor CP decomposition (Q2100536) (← links)
- Large scale tensor regression using kernels and variational inference (Q2102330) (← links)
- Tensor completion via a generalized transformed tensor t-product decomposition without t-SVD (Q2103412) (← links)
- Multi-dimensional image recovery via fully-connected tensor network decomposition under the learnable transforms (Q2103418) (← links)
- The linear span of uniform matrix product states (Q2111081) (← links)
- Efficient low-rank regularization-based algorithms combining advanced techniques for solving tensor completion problems with application to color image recovering (Q2112681) (← links)
- A tensor regularized nuclear norm method for image and video completion (Q2115246) (← links)
- Manifold regularization nonnegative triple decomposition of tensor sets for image compression and representation (Q2116615) (← links)
- QTT-isogeometric solver in two dimensions (Q2123884) (← links)
- High dimensional Riesz space distributed-order advection-dispersion equations with ADI scheme in compression format (Q2127574) (← links)
- Low-rank tensor reconstruction of concentrated densities with application to Bayesian inversion (Q2128063) (← links)
- Nonnegative tensor-train low-rank approximations of the Smoluchowski coagulation equation (Q2128461) (← links)
