Multivariate Rational Approximation via Low-Rank Tensors and the p-AAA Algorithm
Fuente:
arXiv
Guardado en:
| Autores principales: | Balicki, Linus, Gugercin, Serkan |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Multivariate Rational Approximation of Scattered Data Using the p-AAA Algorithm
por: Balicki, Linus, et al.
Publicado: (2025)
por: Balicki, Linus, et al.
Publicado: (2025)
A parametric Keldysh decomposition
por: Balicki, Linus, et al.
Publicado: (2026)
por: Balicki, Linus, et al.
Publicado: (2026)
Time-Domain Iterative Rational Krylov Method
por: Ackermann, Michael S., et al.
Publicado: (2024)
por: Ackermann, Michael S., et al.
Publicado: (2024)
Energy-Based Approximation of Linear Systems with Polynomial Outputs
por: Balicki, Linus, et al.
Publicado: (2024)
por: Balicki, Linus, et al.
Publicado: (2024)
Frequency-Based Reduced Models from Purely Time-Domain Data via Data Informativity
por: Ackermann, Michael S., et al.
Publicado: (2023)
por: Ackermann, Michael S., et al.
Publicado: (2023)
A refined nonlinear least-squares method for the rational approximation problem
por: Ackermann, Michael S., et al.
Publicado: (2026)
por: Ackermann, Michael S., et al.
Publicado: (2026)
Efficient Algorithms for Low Tubal Rank Tensor Approximation with Applications
por: Ahmadi-Asl, Salman, et al.
Publicado: (2024)
por: Ahmadi-Asl, Salman, et al.
Publicado: (2024)
A DEIM Tucker Tensor Cross Algorithm and its Application to Dynamical Low-Rank Approximation
por: Ghahremani, Behzad, et al.
Publicado: (2024)
por: Ghahremani, Behzad, et al.
Publicado: (2024)
Balanced truncation with conformal maps
por: Borghi, Alessandro, et al.
Publicado: (2024)
por: Borghi, Alessandro, et al.
Publicado: (2024)
Randomized Algorithms for Low-Rank Matrix and Tensor Decompositions
por: Pearce, Katherine J., et al.
Publicado: (2025)
por: Pearce, Katherine J., et al.
Publicado: (2025)
A non-intrusive data-based reformulation of a hybrid projection-based model reduction method
por: Gosea, Ion Victor, et al.
Publicado: (2024)
por: Gosea, Ion Victor, et al.
Publicado: (2024)
Interpolatory $\mathcal{H}_2$-optimality Conditions for Structured Linear Time-invariant Systems
por: Mlinarić, Petar, et al.
Publicado: (2023)
por: Mlinarić, Petar, et al.
Publicado: (2023)
Interpolatory Necessary Optimality Conditions for Reduced-order Modeling of Parametric Linear Time-invariant Systems
por: Mlinarić, Petar, et al.
Publicado: (2024)
por: Mlinarić, Petar, et al.
Publicado: (2024)
Provable Low-Rank Tensor-Train Approximations in the Inverse of Large-Scale Structured Matrices
por: Xiao, Chuanfu, et al.
Publicado: (2025)
por: Xiao, Chuanfu, et al.
Publicado: (2025)
Scalable Binary CUR Low-Rank Approximation Algorithm
por: Su, Bowen
Publicado: (2025)
por: Su, Bowen
Publicado: (2025)
HOQRI: Higher-order QR Iteration for Low Multilinear Rank Approximation of Large and Sparse Tensors
por: Sun, Yuchen, et al.
Publicado: (2025)
por: Sun, Yuchen, et al.
Publicado: (2025)
Interpolatory Approximations of PMU Data: Dimension Reduction and Pilot Selection
por: Reiter, Sean, et al.
Publicado: (2025)
por: Reiter, Sean, et al.
Publicado: (2025)
Local Interpolation via Low-Rank Tensor Trains
por: Guzman, Siddhartha E., et al.
Publicado: (2026)
por: Guzman, Siddhartha E., et al.
Publicado: (2026)
Superfast Low Rank Approximation
por: Go, Soo, et al.
Publicado: (2018)
por: Go, Soo, et al.
Publicado: (2018)
CUR Low Rank Approximation of a Matrix at Sublinear Cost
por: Go, Soo, et al.
Publicado: (2019)
por: Go, Soo, et al.
Publicado: (2019)
Low Rank Approximation at Sublinear Cost
por: Luan, Qi, et al.
Publicado: (2019)
por: Luan, Qi, et al.
Publicado: (2019)
Data-driven balanced truncation for linear systems with quadratic outputs
por: Padhi, Reetish, et al.
Publicado: (2025)
por: Padhi, Reetish, et al.
Publicado: (2025)
QRP Variation of Cross--Approximation Iterations for Low Rank Approximation
por: Pan, Victor Y., et al.
Publicado: (2018)
por: Pan, Victor Y., et al.
Publicado: (2018)
Iterative Refinement and Oversampling for Low Rank Approximation
por: Pan, Victor Y., et al.
Publicado: (2019)
por: Pan, Victor Y., et al.
Publicado: (2019)
Low-Rank Approximation by Randomly Pivoted LU
por: Gilles, Marc Aurèle, et al.
Publicado: (2026)
por: Gilles, Marc Aurèle, et al.
Publicado: (2026)
IRKA is a Riemannian Gradient Descent Method
por: Mlinarić, Petar, et al.
Publicado: (2023)
por: Mlinarić, Petar, et al.
Publicado: (2023)
A Novel Transformed Fibered Rank Approximation with Total Variation Regularization for Tensor Completion
por: Chen, Ziming, et al.
Publicado: (2025)
por: Chen, Ziming, et al.
Publicado: (2025)
Second-order AAA algorithms for structured data-driven modeling
por: Ackermann, Michael S., et al.
Publicado: (2025)
por: Ackermann, Michael S., et al.
Publicado: (2025)
A Normal Form Algorithm for Tensor Rank Decomposition
por: Telen, Simon, et al.
Publicado: (2021)
por: Telen, Simon, et al.
Publicado: (2021)
Dynamical Low-Rank Approximation Strategies for Nonlinear Feedback Control Problems
por: Saluzzi, Luca, et al.
Publicado: (2025)
por: Saluzzi, Luca, et al.
Publicado: (2025)
Operator SVD with Neural Networks via Nested Low-Rank Approximation
por: Ryu, J. Jon, et al.
Publicado: (2024)
por: Ryu, J. Jon, et al.
Publicado: (2024)
Precision-induced Adaptive Randomized Low-Rank Approximation for SVD and Matrix Inversion
por: Xu, Weiwei, et al.
Publicado: (2026)
por: Xu, Weiwei, et al.
Publicado: (2026)
Efficient Orthogonal Decomposition with Automatic Basis Extraction for Low-Rank Matrix Approximation
por: Shen, Weijie, et al.
Publicado: (2024)
por: Shen, Weijie, et al.
Publicado: (2024)
Wavelet-Based Observables for Koopman Analysis: An Extended Dynamic Mode Decomposition Framework
por: Tilki, Cankat, et al.
Publicado: (2026)
por: Tilki, Cankat, et al.
Publicado: (2026)
Traffic Flow Data Completion and Anomaly Diagnosis via Sparse and Low-Rank Tensor Optimization
por: Man, Junxi, et al.
Publicado: (2025)
por: Man, Junxi, et al.
Publicado: (2025)
A Novel Adaptive Low-Rank Matrix Approximation Method for Image Compression and Reconstruction
por: Xu, Weiwei, et al.
Publicado: (2025)
por: Xu, Weiwei, et al.
Publicado: (2025)
Cross Interpolation for Solving High-Dimensional Dynamical Systems on Low-Rank Tucker and Tensor Train Manifolds
por: Ghahremani, Behzad, et al.
Publicado: (2024)
por: Ghahremani, Behzad, et al.
Publicado: (2024)
Scalable Computation of Energy Functions for Nonlinear Balanced Truncation
por: Kramer, Boris, et al.
Publicado: (2022)
por: Kramer, Boris, et al.
Publicado: (2022)
High-dimensional Optimization with Low Rank Tensor Sampling and Local Search
por: Sozykin, Konstantin, et al.
Publicado: (2025)
por: Sozykin, Konstantin, et al.
Publicado: (2025)
Pass-efficient Randomized Algorithms for Low-rank Approximation of Quaternion Matrices
por: Ahmadi-Asl, Salman, et al.
Publicado: (2025)
por: Ahmadi-Asl, Salman, et al.
Publicado: (2025)
Ejemplares similares
-
Multivariate Rational Approximation of Scattered Data Using the p-AAA Algorithm
por: Balicki, Linus, et al.
Publicado: (2025) -
A parametric Keldysh decomposition
por: Balicki, Linus, et al.
Publicado: (2026) -
Time-Domain Iterative Rational Krylov Method
por: Ackermann, Michael S., et al.
Publicado: (2024) -
Energy-Based Approximation of Linear Systems with Polynomial Outputs
por: Balicki, Linus, et al.
Publicado: (2024) -
Frequency-Based Reduced Models from Purely Time-Domain Data via Data Informativity
por: Ackermann, Michael S., et al.
Publicado: (2023)