PODNO: Proper Orthogonal Decomposition Neural Operators
Fuente:
arXiv
Saved in:
| Main Authors: | Cheng, Zilan, Wang, Zhongjian, Wang, Li-Lian, Azaiez, Mejdi |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Enhancing Future Prediction of Linear and Nonlinear Reduced-Order Models for Transport-Dominated Problems Using Lagrangian Data
by: Li, Meng, et al.
Published: (2026)
by: Li, Meng, et al.
Published: (2026)
A theoretical analysis on the inversion of matrices via Neural Networks designed with Strassen algorithm
by: Romera, Gonzalo, et al.
Published: (2025)
by: Romera, Gonzalo, et al.
Published: (2025)
Least Squares with Equality constraints Extreme Learning Machines for the resolution of PDEs
by: De Falco, Davide Elia, et al.
Published: (2025)
by: De Falco, Davide Elia, et al.
Published: (2025)
ARDO: A Weak Formulation Deep Neural Network Method for Elliptic and Parabolic PDEs Based on Random Differences of Test Functions
by: Cai, Wei, et al.
Published: (2025)
by: Cai, Wei, et al.
Published: (2025)
Machine Learning-based quadratic closures for non-intrusive Reduced Order Models
by: Codega, Gabriele, et al.
Published: (2025)
by: Codega, Gabriele, et al.
Published: (2025)
The lowest-order Neural Approximated Virtual Element Method on polygonal elements
by: Berrone, Stefano, et al.
Published: (2024)
by: Berrone, Stefano, et al.
Published: (2024)
A Low Rank Neural Representation of Entropy Solutions
by: Rim, Donsub, et al.
Published: (2024)
by: Rim, Donsub, et al.
Published: (2024)
A Structure-Preserving Framework for Solving Parabolic Partial Differential Equations with Neural Networks
by: Chen, Gaohang, et al.
Published: (2025)
by: Chen, Gaohang, et al.
Published: (2025)
Vanilla Feedforward Neural Networks as a Discretization of Dynamical Systems
by: Duan, Yifei, et al.
Published: (2022)
by: Duan, Yifei, et al.
Published: (2022)
Minimum Width of Leaky-ReLU Neural Networks for Uniform Universal Approximation
by: Li, Li'ang, et al.
Published: (2023)
by: Li, Li'ang, et al.
Published: (2023)
Convergence of Physics-Informed Neural Networks for Fully Nonlinear PDE's
by: Arakelyan, Avetik, et al.
Published: (2024)
by: Arakelyan, Avetik, et al.
Published: (2024)
Neural Flow Operators can Approximate any Operator: Abstract Frameworks and Universal Approximations
by: Chen, Shuang, et al.
Published: (2026)
by: Chen, Shuang, et al.
Published: (2026)
A discontinuous Galerkin method for elliptic-hyperbolic equations
by: Perinati, Chiara, et al.
Published: (2026)
by: Perinati, Chiara, et al.
Published: (2026)
RandONet: Shallow-Networks with Random Projections for learning linear and nonlinear operators
by: Fabiani, Gianluca, et al.
Published: (2024)
by: Fabiani, Gianluca, et al.
Published: (2024)
Adaptive Randomized Neural Networks with Locally Activation Function: Theory and Algorithm for Solving PDEs
by: Bi, Ran, et al.
Published: (2026)
by: Bi, Ran, et al.
Published: (2026)
Deep asymptotic expansion method for solving singularly perturbed time-dependent reaction-advection-diffusion equations
by: Zhu, Qiao, et al.
Published: (2025)
by: Zhu, Qiao, et al.
Published: (2025)
Universal approximation property of ODENet and ResNet with a single activation function
by: Kimura, Masato, et al.
Published: (2024)
by: Kimura, Masato, et al.
Published: (2024)
Neural Network Element Method for Partial Differential Equations
by: Wang, Yifan, et al.
Published: (2025)
by: Wang, Yifan, et al.
Published: (2025)
Regularity Analysis and Tensor Neural Network Methods for Quasiperiodic Elliptic Equations
by: Ren, Jingze, et al.
Published: (2026)
by: Ren, Jingze, et al.
Published: (2026)
A reduced order Schwarz method for nonlinear multiscale elliptic equations based on two-layer neural networks
by: Chen, Shi, et al.
Published: (2021)
by: Chen, Shi, et al.
Published: (2021)
Solving High Dimensional Partial Differential Equations Using Tensor Neural Network and A Posteriori Error Estimators
by: Wang, Yifan, et al.
Published: (2023)
by: Wang, Yifan, et al.
Published: (2023)
A neural network method for scalar conservation laws with convergence rates for shock-wave solutions
by: Cao, Jiachuan, et al.
Published: (2026)
by: Cao, Jiachuan, et al.
Published: (2026)
Equidistribution-based training of Free Knot Splines and ReLU Neural Networks
by: Appella, Simone, et al.
Published: (2024)
by: Appella, Simone, et al.
Published: (2024)
Discretization Error of Fourier Neural Operators
by: Lanthaler, Samuel, et al.
Published: (2024)
by: Lanthaler, Samuel, et al.
Published: (2024)
Learning WENO for entropy stable schemes to solve conservation laws
by: Charles, Philip, et al.
Published: (2024)
by: Charles, Philip, et al.
Published: (2024)
Entropy-based convergence rates of greedy algorithms
by: Li, Yuwen, et al.
Published: (2023)
by: Li, Yuwen, et al.
Published: (2023)
Arbitrary-order pressure-robust DDR and VEM methods for the Stokes problem on polyhedral meshes
by: da Veiga, Lourenço Beirão, et al.
Published: (2021)
by: da Veiga, Lourenço Beirão, et al.
Published: (2021)
Learning on the Temporal Tangent Bundle for Physics-Informed Neural Networks
by: Jamal, Adetola, et al.
Published: (2026)
by: Jamal, Adetola, et al.
Published: (2026)
Neural Network Dual Norms for Minimal Residual Finite Element Methods
by: Alsobhi, Hamd, et al.
Published: (2025)
by: Alsobhi, Hamd, et al.
Published: (2025)
Geometric Generalization of Neural Operators from Kernel Integral Perspective
by: Han, Mingyu, et al.
Published: (2026)
by: Han, Mingyu, et al.
Published: (2026)
Prediction of discretization of online GMsFEM using deep learning for Richards equation
by: Spiridonov, Denis, et al.
Published: (2024)
by: Spiridonov, Denis, et al.
Published: (2024)
A Localized Orthogonal Decomposition Method for Heterogeneous Stokes Problems
by: Hauck, Moritz, et al.
Published: (2024)
by: Hauck, Moritz, et al.
Published: (2024)
Solving Inverse PDE Problems using Minimization Methods and AI
by: Helwani, Noura Al, et al.
Published: (2026)
by: Helwani, Noura Al, et al.
Published: (2026)
Neural-HSS: Hierarchical Semi-Separable Neural PDE Solver
by: Sittoni, Pietro, et al.
Published: (2026)
by: Sittoni, Pietro, et al.
Published: (2026)
Neural enrichment finite element method: A hybrid framework for problems with strong oscillations or interface problems
by: Guo, Shihan, et al.
Published: (2026)
by: Guo, Shihan, et al.
Published: (2026)
Sparse and low-rank approximations of parametric elliptic PDEs: the best of both worlds
by: Bachmayr, Markus, et al.
Published: (2025)
by: Bachmayr, Markus, et al.
Published: (2025)
Enforcing boundary conditions for physics-informed neural operators
by: Göschel, Niklas, et al.
Published: (2025)
by: Göschel, Niklas, et al.
Published: (2025)
Convergent Operator-Splitting Scheme for Viscosity Solutions: A Foundation for Learning Domain-to-Solution Maps
by: Wu, Po-Yi
Published: (2025)
by: Wu, Po-Yi
Published: (2025)
A High-Order Localized Orthogonal Decomposition Method for Heterogeneous Stokes Problems
by: Hauck, Moritz, et al.
Published: (2025)
by: Hauck, Moritz, et al.
Published: (2025)
Operator Inference for Elliptic Eigenvalue Problems
by: Li, Haoqian, et al.
Published: (2025)
by: Li, Haoqian, et al.
Published: (2025)
Similar Items
-
Enhancing Future Prediction of Linear and Nonlinear Reduced-Order Models for Transport-Dominated Problems Using Lagrangian Data
by: Li, Meng, et al.
Published: (2026) -
A theoretical analysis on the inversion of matrices via Neural Networks designed with Strassen algorithm
by: Romera, Gonzalo, et al.
Published: (2025) -
Least Squares with Equality constraints Extreme Learning Machines for the resolution of PDEs
by: De Falco, Davide Elia, et al.
Published: (2025) -
ARDO: A Weak Formulation Deep Neural Network Method for Elliptic and Parabolic PDEs Based on Random Differences of Test Functions
by: Cai, Wei, et al.
Published: (2025) -
Machine Learning-based quadratic closures for non-intrusive Reduced Order Models
by: Codega, Gabriele, et al.
Published: (2025)