Linear Stability Analysis of Physics-Informed Random Projection Neural Networks for ODEs
Fuente:
arXiv
Saved in:
| Main Authors: | Fabiani, Gianluca, Bollt, Erik, Siettos, Constantinos, Yannacopoulos, Athanasios N. |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
A physics-informed neural network method for the approximation of slow invariant manifolds for the general class of stiff systems of ODEs
by: Patsatzis, Dimitrios G., et al.
Published: (2024)
by: Patsatzis, Dimitrios G., et al.
Published: (2024)
Slow Invariant Manifolds of Singularly Perturbed Systems via Physics-Informed Machine Learning
by: Patsatzis, Dimitrios G., et al.
Published: (2023)
by: Patsatzis, Dimitrios G., et al.
Published: (2023)
Stability and Bifurcation Analysis of Nonlinear PDEs via Random Projection-based PINNs: A Krylov-Arnoldi Approach
by: Fabiani, Gianluca, et al.
Published: (2026)
by: Fabiani, Gianluca, et al.
Published: (2026)
Fredholm Neural Networks
by: Georgiou, Kyriakos, et al.
Published: (2024)
by: Georgiou, Kyriakos, et al.
Published: (2024)
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)
GoRINNs: Godunov-Riemann Informed Neural Networks for Learning Hyperbolic Conservation Laws
by: Patsatzis, Dimitrios G., et al.
Published: (2024)
by: Patsatzis, Dimitrios G., et al.
Published: (2024)
Nonlinear Discrete-Time Observers with Physics-Informed Neural Networks
by: Alvarez, Hector Vargas, et al.
Published: (2024)
by: Alvarez, Hector Vargas, et al.
Published: (2024)
Rodas6P and Tsit5DA - two new Rosenbrock-type methods for DAEs
by: Steinebach, Gerd
Published: (2025)
by: Steinebach, Gerd
Published: (2025)
A Low-complexity Structured Neural Network to Realize States of Dynamical Systems
by: Aluvihare, Hansaka, et al.
Published: (2025)
by: Aluvihare, Hansaka, et al.
Published: (2025)
Learn and Verify: A Framework for Rigorous Verification of Physics-Informed Neural Networks
by: Tanaka, Kazuaki, et al.
Published: (2026)
by: Tanaka, Kazuaki, et al.
Published: (2026)
Development and Analysis of Chien-Physics-Informed Neural Networks for Singular Perturbation Problems
by: Singh, Gautam, et al.
Published: (2025)
by: Singh, Gautam, et al.
Published: (2025)
Subspace method based on neural networks for eigenvalue problems
by: Dai, Xiaoying, et al.
Published: (2024)
by: Dai, Xiaoying, et al.
Published: (2024)
Stability theory of TASE-Runge-Kutta methods with inexact Jacobian
by: Conte, D., et al.
Published: (2024)
by: Conte, D., 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)
Invariant Manifolds of Discrete-time Dynamical Systems with Nonlinear Exosystems via Hybrid Physics-Informed Neural Networks
by: Patsatzis, Dimitrios G., et al.
Published: (2025)
by: Patsatzis, Dimitrios G., et al.
Published: (2025)
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)
Physics-Informed Neural Networks: Bridging the Divide Between Conservative and Non-Conservative Equations
by: Neelan, Arun Govind, et al.
Published: (2025)
by: Neelan, Arun Govind, et al.
Published: (2025)
Deep Learning Based on Randomized Quasi-Monte Carlo Method for Solving Linear Kolmogorov Partial Differential Equation
by: Xiao, Jichang, et al.
Published: (2023)
by: Xiao, Jichang, et al.
Published: (2023)
The Neural Approximated Virtual Element Method for Elasticity Problems
by: Berrone, Stefano, et al.
Published: (2025)
by: Berrone, Stefano, et al.
Published: (2025)
A New Class of General Linear Method with Inherent Quadratic Stability for Solving Stiff Differential Systems
by: Gautam, Sakshi, et al.
Published: (2025)
by: Gautam, Sakshi, et al.
Published: (2025)
Randomized methods for dynamical low-rank approximation
by: Carrel, Benjamin
Published: (2024)
by: Carrel, Benjamin
Published: (2024)
Error estimation for numerical approximations of ODEs via composition techniques. Part I: One-step methods
by: Deeb, Ahmad, et al.
Published: (2024)
by: Deeb, Ahmad, et al.
Published: (2024)
Equation-Free Coarse Control of Distributed Parameter Systems via Local Neural Operators
by: Fabiani, Gianluca, et al.
Published: (2025)
by: Fabiani, Gianluca, et al.
Published: (2025)
Preconditioning and Linearly Implicit Time Integration for the Serre-Green-Naghdi Equations
by: Feng, Linwan, et al.
Published: (2025)
by: Feng, Linwan, et al.
Published: (2025)
Error analyses of Sinc-collocation methods for exponential decay initial value problems
by: Okayama, Tomoaki, et al.
Published: (2023)
by: Okayama, Tomoaki, et al.
Published: (2023)
Data-driven modelling of brain activity using neural networks, Diffusion Maps, and the Koopman operator
by: Gallos, Ioannis K., et al.
Published: (2023)
by: Gallos, Ioannis K., et al.
Published: (2023)
Learning Contractive Integral Operators with Fredholm Integral Neural Operators
by: Georgiou, Kyriakos C., et al.
Published: (2026)
by: Georgiou, Kyriakos C., et al.
Published: (2026)
Error estimation for numerical approximations of ODEs via composition techniques. Part II: BDF methods
by: Deeb, Ahmad, et al.
Published: (2026)
by: Deeb, Ahmad, et al.
Published: (2026)
A discontinuous Galerkin plane wave neural network method for Helmholtz equation and Maxwell's equations
by: Yuan, Long, et al.
Published: (2025)
by: Yuan, Long, et al.
Published: (2025)
Discontinuous hybrid neural networks for the one-dimensional partial differential equations
by: Wang, Xiaoyu, et al.
Published: (2025)
by: Wang, Xiaoyu, et al.
Published: (2025)
A framework of discontinuous Galerkin neural networks for iteratively approximating residuals
by: Yuan, Long, et al.
Published: (2025)
by: Yuan, Long, et al.
Published: (2025)
Neural Ordinary Differential Equations for Model Order Reduction of Stiff Systems
by: Caldana, Matteo, et al.
Published: (2024)
by: Caldana, Matteo, et al.
Published: (2024)
Neural Network Dual Norms for Minimal Residual Finite Element Methods
by: Alsobhi, Hamd, et al.
Published: (2025)
by: Alsobhi, Hamd, et al.
Published: (2025)
Finite-Time Analysis of Crises in a Chaotically Forced Ocean Model
by: Axelsen, Andrew R., et al.
Published: (2023)
by: Axelsen, Andrew R., et al.
Published: (2023)
Self-adaptive physics-informed neural network for forward and inverse problems in heterogeneous porous flow
by: Aziz, Md. Abdul, et al.
Published: (2025)
by: Aziz, Md. Abdul, et al.
Published: (2025)
MAGNET: an open-source library for mesh agglomeration by Graph Neural Networks
by: Antonietti, Paola F., et al.
Published: (2025)
by: Antonietti, Paola F., et al.
Published: (2025)
Data-Free Asymptotics-Informed Operator Networks for Singularly Perturbed PDEs
by: Lee, Jinsil, et al.
Published: (2025)
by: Lee, Jinsil, et al.
Published: (2025)
Neural Preconditioned Born Series: A Metric-Matched Framework for Learning-based Preconditioners
by: Wang, Juntao, et al.
Published: (2026)
by: Wang, Juntao, et al.
Published: (2026)
Multi-Order Monte Carlo IMEX hierarchies for uncertainty quantification in multiscale hyperbolic systems
by: Bertaglia, Giulia, et al.
Published: (2025)
by: Bertaglia, Giulia, et al.
Published: (2025)
Similar Items
-
A physics-informed neural network method for the approximation of slow invariant manifolds for the general class of stiff systems of ODEs
by: Patsatzis, Dimitrios G., et al.
Published: (2024) -
Slow Invariant Manifolds of Singularly Perturbed Systems via Physics-Informed Machine Learning
by: Patsatzis, Dimitrios G., et al.
Published: (2023) -
Stability and Bifurcation Analysis of Nonlinear PDEs via Random Projection-based PINNs: A Krylov-Arnoldi Approach
by: Fabiani, Gianluca, et al.
Published: (2026) -
Fredholm Neural Networks
by: Georgiou, Kyriakos, et al.
Published: (2024) -
RandONet: Shallow-Networks with Random Projections for learning linear and nonlinear operators
by: Fabiani, Gianluca, et al.
Published: (2024)