A Fully Probabilistic Tensor Network for Regularized Volterra System Identification
Fuente:
arXiv
Saved in:
| Main Authors: | Kilic, Afra, Batselier, Kim |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Interpretable Bayesian Tensor Network Kernel Machines with Automatic Rank and Feature Selection
by: Kilic, Afra, et al.
Published: (2025)
by: Kilic, Afra, et al.
Published: (2025)
Laplace Approximation For Tensor Train Kernel Machines In System Identification
by: Saiapin, Albert, et al.
Published: (2025)
by: Saiapin, Albert, et al.
Published: (2025)
Tensor Network Based Feature Learning Model
by: Saiapin, Albert, et al.
Published: (2025)
by: Saiapin, Albert, et al.
Published: (2025)
Laplace Approximation for Bayesian Tensor Network Kernel Machines
by: Saiapin, Albert, et al.
Published: (2026)
by: Saiapin, Albert, et al.
Published: (2026)
Tensor Network-Constrained Kernel Machines as Gaussian Processes
by: Wesel, Frederiek, et al.
Published: (2024)
by: Wesel, Frederiek, et al.
Published: (2024)
Quantized Fourier and Polynomial Features for more Expressive Tensor Network Models
by: Wesel, Frederiek, et al.
Published: (2023)
by: Wesel, Frederiek, et al.
Published: (2023)
Automatic Structure Identification for Highly Nonlinear MIMO Volterra Tensor Networks
by: Memmel, Eva, et al.
Published: (2025)
by: Memmel, Eva, et al.
Published: (2025)
Tensor network square root Kalman filter for online Gaussian process regression
by: Menzen, Clara, et al.
Published: (2024)
by: Menzen, Clara, et al.
Published: (2024)
A Kernelizable Primal-Dual Formulation of the Multilinear Singular Value Decomposition
by: Wesel, Frederiek, et al.
Published: (2024)
by: Wesel, Frederiek, et al.
Published: (2024)
Position: Tensor Networks are a Valuable Asset for Green AI
by: Memmel, Eva, et al.
Published: (2022)
by: Memmel, Eva, et al.
Published: (2022)
Constructing structured tensor priors for Bayesian inverse problems
by: Batselier, Kim
Published: (2024)
by: Batselier, Kim
Published: (2024)
Efficient Probabilistic Tensor Networks
by: Hameed, Marawan Gamal Abdel, et al.
Published: (2025)
by: Hameed, Marawan Gamal Abdel, et al.
Published: (2025)
Probabilistic Inference in the Era of Tensor Networks and Differential Programming
by: Roa-Villescas, Martin, et al.
Published: (2024)
by: Roa-Villescas, Martin, et al.
Published: (2024)
Mixup Regularization: A Probabilistic Perspective
by: El-Laham, Yousef, et al.
Published: (2025)
by: El-Laham, Yousef, et al.
Published: (2025)
Matrix Completion via Nonsmooth Regularization of Fully Connected Neural Networks
by: Faramarzi, Sajad, et al.
Published: (2024)
by: Faramarzi, Sajad, et al.
Published: (2024)
Tensor-Networks-based Learning of Probabilistic Cellular Automata Dynamics
by: Casagrande, Heitor P., et al.
Published: (2024)
by: Casagrande, Heitor P., et al.
Published: (2024)
Wasserstein Nonnegative Tensor Factorization with Manifold Regularization
by: Wang, Jianyu, et al.
Published: (2024)
by: Wang, Jianyu, et al.
Published: (2024)
SVDinsTN: A Tensor Network Paradigm for Efficient Structure Search from Regularized Modeling Perspective
by: Zheng, Yu-Bang, et al.
Published: (2023)
by: Zheng, Yu-Bang, et al.
Published: (2023)
Probabilistic Numeric SMC Sampling for Bayesian Nonlinear System Identification in Continuous Time
by: Longbottom, Joe D., et al.
Published: (2024)
by: Longbottom, Joe D., et al.
Published: (2024)
Low-Rank Tensor Learning by Generalized Nonconvex Regularization
by: Xia, Sijia, et al.
Published: (2024)
by: Xia, Sijia, et al.
Published: (2024)
VibeTensor: System Software for Deep Learning, Fully Generated by AI Agents
by: Xu, Bing, et al.
Published: (2026)
by: Xu, Bing, et al.
Published: (2026)
A Unified Regularization Approach to High-Dimensional Generalized Tensor Bandits
by: Li, Jiannan, et al.
Published: (2025)
by: Li, Jiannan, et al.
Published: (2025)
Toward Understanding Convolutional Neural Networks from Volterra Convolution Perspective
by: Li, Tenghui, et al.
Published: (2021)
by: Li, Tenghui, et al.
Published: (2021)
Accelerating Large-Scale Regularized High-Order Tensor Recovery
by: Qin, Wenjin, et al.
Published: (2025)
by: Qin, Wenjin, et al.
Published: (2025)
Efficient Approximation of Volterra Series for High-Dimensional Systems
by: Khoshnan, Navin, et al.
Published: (2025)
by: Khoshnan, Navin, et al.
Published: (2025)
Reservoir kernels and Volterra series
by: Gonon, Lukas, et al.
Published: (2022)
by: Gonon, Lukas, et al.
Published: (2022)
Riemann Tensor Neural Networks: Learning Conservative Systems with Physics-Constrained Networks
by: Jnini, Anas, et al.
Published: (2025)
by: Jnini, Anas, et al.
Published: (2025)
Noise-Augmented $\ell_0$ Regularization of Tensor Regression with Tucker Decomposition
by: Yan, Tian, et al.
Published: (2023)
by: Yan, Tian, et al.
Published: (2023)
Representation Disentaglement via Regularization by Causal Identification
by: Castorena, Juan
Published: (2023)
by: Castorena, Juan
Published: (2023)
Enforcing Calibration in Multi-Output Probabilistic Regression with Pre-rank Regularization
by: Desobry, Naomi, et al.
Published: (2025)
by: Desobry, Naomi, et al.
Published: (2025)
Tensor Completion Leveraging Graph Information: A Dynamic Regularization Approach with Statistical Guarantees
by: Wang, Kaidong, et al.
Published: (2023)
by: Wang, Kaidong, et al.
Published: (2023)
A Robust Probabilistic Approach to Stochastic Subspace Identification
by: O'Connell, Brandon J., et al.
Published: (2023)
by: O'Connell, Brandon J., et al.
Published: (2023)
Factor Augmented Tensor-on-Tensor Neural Networks
by: Zhou, Guanhao, et al.
Published: (2024)
by: Zhou, Guanhao, et al.
Published: (2024)
Fully Distributed, Flexible Compositional Visual Representations via Soft Tensor Products
by: Sun, Bethia, et al.
Published: (2024)
by: Sun, Bethia, et al.
Published: (2024)
Tensor-Compressed and Fully-Quantized Training of Neural PDE Solvers
by: Lu, Jinming, et al.
Published: (2025)
by: Lu, Jinming, et al.
Published: (2025)
Randomized Transport Plans via Hierarchical Fully Probabilistic Design
by: Y., Sarah Boufelja, et al.
Published: (2024)
by: Y., Sarah Boufelja, et al.
Published: (2024)
Phoenix: A Federated Generative Diffusion Model
by: Jothiraj, Fiona Victoria Stanley, et al.
Published: (2023)
by: Jothiraj, Fiona Victoria Stanley, et al.
Published: (2023)
Tensor Convolutional Network for Higher-Order Interaction Prediction in Sparse Tensors
by: Jang, Jun-Gi, et al.
Published: (2025)
by: Jang, Jun-Gi, et al.
Published: (2025)
Probabilistic Functional Neural Networks
by: Wang, Haixu, et al.
Published: (2025)
by: Wang, Haixu, et al.
Published: (2025)
Probabilistic Kolmogorov-Arnold Network
by: Polar, Andrew, et al.
Published: (2021)
by: Polar, Andrew, et al.
Published: (2021)
Similar Items
-
Interpretable Bayesian Tensor Network Kernel Machines with Automatic Rank and Feature Selection
by: Kilic, Afra, et al.
Published: (2025) -
Laplace Approximation For Tensor Train Kernel Machines In System Identification
by: Saiapin, Albert, et al.
Published: (2025) -
Tensor Network Based Feature Learning Model
by: Saiapin, Albert, et al.
Published: (2025) -
Laplace Approximation for Bayesian Tensor Network Kernel Machines
by: Saiapin, Albert, et al.
Published: (2026) -
Tensor Network-Constrained Kernel Machines as Gaussian Processes
by: Wesel, Frederiek, et al.
Published: (2024)