The following pages link to Tensor-Train Decomposition (Q126157):
Displaying 50 items.
- Tensor networks for MIMO LPV system identification (Q5221376) (← links)
- A Hybrid Alternating Least Squares--TT-Cross Algorithm for Parametric PDEs (Q5228358) (← links)
- Convergence of a Low-Rank Lie--Trotter Splitting for Stiff Matrix Differential Equations (Q5232313) (← links)
- A Geometric Description of Feasible Singular Values in the Tensor Train Format (Q5237904) (← links)
- Preconditioners and Tensor Product Solvers for Optimal Control Problems from Chemotaxis (Q5243525) (← links)
- Time Integration of Tensor Trains (Q5253597) (← links)
- Fast Multidimensional Convolution in Low-Rank Tensor Formats via Cross Approximation (Q5254416) (← links)
- Tensor Spaces and Hierarchical Tensor Representations (Q5256562) (← links)
- Corrected One-Site Density Matrix Renormalization Group and Alternating Minimal Energy Algorithm (Q5264857) (← links)
- Estimating a Few Extreme Singular Values and Vectors for Large-Scale Matrices in Tensor Train Format (Q5265006) (← links)
- Computing Sparse Representations of Multidimensional Signals Using Kronecker Bases (Q5327163) (← links)
- Cubature, Approximation, and Isotropy in the Hypercube (Q5348327) (← links)
- Recompression of Hadamard Products of Tensors in Tucker Format (Q5357970) (← links)
- Structure-Preserving Low Multilinear Rank Approximation of Antisymmetric Tensors (Q5358301) (← links)
- Chebfun in Three Dimensions (Q5358959) (← links)
- Deep Convolutional Neural Networks for Image Classification: A Comprehensive Review (Q5382481) (← links)
- A Semi-Lagrangian Vlasov Solver in Tensor Train Format (Q5502085) (← links)
- Fast low‐rank approximations of multidimensional integrals in ion‐atomic collisions modelling (Q5739747) (← links)
- Fast tensor method for summation of long‐range potentials on 3D lattices with defects (Q5739760) (← links)
- Preconditioned Low-rank Riemannian Optimization for Linear Systems with Tensor Product Structure (Q5739957) (← links)
- Reduced Basis Methods: From Low-Rank Matrices to Low-Rank Tensors (Q5739958) (← links)
- Tensor numerical methods for multidimensional PDES: theoretical analysis and initial applications (Q5744910) (← links)
- Multilinear Control Systems Theory (Q5853636) (← links)
- Nonlocal robust tensor recovery with nonconvex regularization <sup>*</sup> (Q5854060) (← links)
- The matrix product approximation for the dynamic cavity method (Q5856231) (← links)
- Computing Eigenspaces With Low Rank Constraints (Q5857626) (← links)
- Robust Alternating Direction Implicit Solver in Quantized Tensor Formats for a Three-Dimensional Elliptic PDE (Q5857728) (← links)
- On the Compressibility of Tensors (Q5857845) (← links)
- New Riemannian Preconditioned Algorithms for Tensor Completion via Polyadic Decomposition (Q5863880) (← links)
- Approximative Policy Iteration for Exit Time Feedback Control Problems Driven by Stochastic Differential Equations using Tensor Train Format (Q5865245) (← links)
- Higher-Order QR with Tournament Pivoting for Tensor Compression (Q5885806) (← links)
- Randomized Algorithms for Rounding in the Tensor-Train Format (Q5886850) (← links)
- Low-rank approximation of continuous functions in Sobolev spaces with dominating mixed smoothness (Q5886873) (← links)
- Orthogonal decomposition of tensor trains (Q5888857) (← links)
- Finding stationary points on bounded-rank matrices: a geometric hurdle and a smooth remedy (Q6038660) (← links)
- Adaptive Nonintrusive Reconstruction of Solutions to High-Dimensional Parametric PDEs (Q6039259) (← links)
- Low-rank tensor structure preservation in fractional operators by means of exponential sums (Q6040879) (← links)
- Generative modeling via tree tensor network states (Q6042367) (← links)
- Algebraic compressed sensing (Q6042618) (← links)
- Low-rank tensor methods for partial differential equations (Q6047498) (← links)
- Overcoming the timescale barrier in molecular dynamics: Transfer operators, variational principles and machine learning (Q6047503) (← links)
- The condition number of many tensor decompositions is invariant under Tucker compression (Q6047573) (← links)
- Generative modeling via tensor train sketching (Q6051158) (← links)
- Data-Driven Tensor Train Gradient Cross Approximation for Hamilton–Jacobi–Bellman Equations (Q6054276) (← links)
- Noniterative tensor network‐based algorithm for Volterra system identification (Q6063766) (← links)
- A literature survey of matrix methods for data science (Q6068265) (← links)
- Modeling nonlinear systems using the tensor network B‐spline and the multi‐innovation identification theory (Q6069269) (← links)
- Adaptive experimental design for multi‐fidelity surrogate modeling of multi‐disciplinary systems (Q6069984) (← links)
- Group-Invariant Tensor Train Networks for Supervised Learning (Q6070296) (← links)
- State estimation in nonlinear parametric time dependent systems using tensor train (Q6071444) (← links)
