Error estimation for physics-informed neural networks with implicit Runge-Kutta methods
Fuente:
arXiv
Guardado en:
| Autores principales: | Stiasny, Jochen, Chatzivasileiadis, Spyros |
|---|---|
| Formato: | Preprint |
| Publicado: |
2024
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
PINNSim: A Simulator for Power System Dynamics based on Physics-Informed Neural Networks
por: Stiasny, Jochen, et al.
Publicado: (2023)
por: Stiasny, Jochen, et al.
Publicado: (2023)
Correctness Verification of Neural Networks Approximating Differential Equations
por: Ellinas, Petros, et al.
Publicado: (2024)
por: Ellinas, Petros, et al.
Publicado: (2024)
Physics-Informed Neural Networks: a Plug and Play Integration into Power System Dynamic Simulations
por: Nadal, Ignasi Ventura, et al.
Publicado: (2024)
por: Nadal, Ignasi Ventura, et al.
Publicado: (2024)
Learning phase-space flows using time-discrete implicit Runge-Kutta PINNs
por: Corral, Álvaro Fernández, et al.
Publicado: (2024)
por: Corral, Álvaro Fernández, et al.
Publicado: (2024)
Global Performance Guarantees for Neural Network Models of AC Power Flow
por: Chevalier, Samuel, et al.
Publicado: (2022)
por: Chevalier, Samuel, et al.
Publicado: (2022)
Control of dynamical systems with neural networks
por: Böttcher, Lucas
Publicado: (2025)
por: Böttcher, Lucas
Publicado: (2025)
Controlled oscillation modeling using port-Hamiltonian neural networks
por: Linares, Maximino, et al.
Publicado: (2026)
por: Linares, Maximino, et al.
Publicado: (2026)
Identifying the nonlinear string dynamics with port-Hamiltonian neural networks
por: Linares, Maximino, et al.
Publicado: (2026)
por: Linares, Maximino, et al.
Publicado: (2026)
Residual Power Flow for Neural Solvers
por: Stiasny, Jochen, et al.
Publicado: (2026)
por: Stiasny, Jochen, et al.
Publicado: (2026)
Physics-informed State-space Neural Networks for Transport Phenomena
por: Dave, Akshay J., et al.
Publicado: (2023)
por: Dave, Akshay J., et al.
Publicado: (2023)
Verification and Validation of Physics-Informed Surrogate Component Models for Dynamic Power-System Simulation
por: Ellinas, Petros, et al.
Publicado: (2026)
por: Ellinas, Petros, et al.
Publicado: (2026)
Stabilization of nonlinear systems with unknown delays via delay-adaptive neural operator approximate predictors
por: Bhan, Luke, et al.
Publicado: (2025)
por: Bhan, Luke, et al.
Publicado: (2025)
Observability conditions for neural state-space models with eigenvalues and their roots of unity
por: Gracyk, Andrew
Publicado: (2025)
por: Gracyk, Andrew
Publicado: (2025)
A Physics-informed Machine Learning-based Control Method for Nonlinear Dynamic Systems with Highly Noisy Measurements
por: Ma, Mason, et al.
Publicado: (2023)
por: Ma, Mason, et al.
Publicado: (2023)
Delay compensation of multi-input distinct delay nonlinear systems via neural operators
por: Bajraktari, Filip, et al.
Publicado: (2025)
por: Bajraktari, Filip, et al.
Publicado: (2025)
Model-Based Reinforcement Learning Control of Reaction-Diffusion Problems
por: Schenk, Christina, et al.
Publicado: (2024)
por: Schenk, Christina, et al.
Publicado: (2024)
Multi evolutional deep neural networks (Multi-EDNN)
por: Kim, Hadden, et al.
Publicado: (2024)
por: Kim, Hadden, et al.
Publicado: (2024)
WGFINNs: Weak formulation-based GENERIC formalism informed neural networks
por: Park, Jun Sur Richard, et al.
Publicado: (2026)
por: Park, Jun Sur Richard, et al.
Publicado: (2026)
A hybrid Quantum-Classical Algorithm for Mixed-Integer Optimization in Power Systems
por: Ellinas, Petros, et al.
Publicado: (2024)
por: Ellinas, Petros, et al.
Publicado: (2024)
Stochastic Quantum Power Flow for Risk Assessment in Power Systems
por: Sævarsson, Brynjar, et al.
Publicado: (2023)
por: Sævarsson, Brynjar, et al.
Publicado: (2023)
Approaching epidemiological dynamics of COVID-19 with physics-informed neural networks
por: Han, Shuai, et al.
Publicado: (2023)
por: Han, Shuai, et al.
Publicado: (2023)
Trustworthiness Layer for Foundation Models in Power Systems: Application to N-k Contingency Screening
por: Alcántara, Antonio, et al.
Publicado: (2026)
por: Alcántara, Antonio, et al.
Publicado: (2026)
Iterative Learning Control of Fast, Nonlinear, Oscillatory Dynamics (Preprint)
por: Brooks, John W., et al.
Publicado: (2024)
por: Brooks, John W., et al.
Publicado: (2024)
Stochastic Reinforcement Learning with Stability Guarantees for Control of Unknown Nonlinear Systems
por: Quartz, Thanin, et al.
Publicado: (2024)
por: Quartz, Thanin, et al.
Publicado: (2024)
Learning Deep Dissipative Dynamics
por: Okamoto, Yuji, et al.
Publicado: (2024)
por: Okamoto, Yuji, et al.
Publicado: (2024)
Learning Koopman-based Stability Certificates for Unknown Nonlinear Systems
por: Zhou, Ruikun, et al.
Publicado: (2024)
por: Zhou, Ruikun, et al.
Publicado: (2024)
Reservoir computing for system identification and predictive control with limited data
por: Williams, Jan P., et al.
Publicado: (2024)
por: Williams, Jan P., et al.
Publicado: (2024)
Uncertainty Modelling and Robust Observer Synthesis using the Koopman Operator
por: Dahdah, Steven, et al.
Publicado: (2024)
por: Dahdah, Steven, et al.
Publicado: (2024)
Gradient Flow Equations for Deep Linear Neural Networks: A Survey from a Network Perspective
por: Wendin, Joel, et al.
Publicado: (2025)
por: Wendin, Joel, et al.
Publicado: (2025)
On Data-Driven Koopman Representations of Nonlinear Delay Differential Equations
por: Rajkumar, Santosh Mohan, et al.
Publicado: (2026)
por: Rajkumar, Santosh Mohan, et al.
Publicado: (2026)
Closed-Loop Koopman Operator Approximation
por: Dahdah, Steven, et al.
Publicado: (2023)
por: Dahdah, Steven, et al.
Publicado: (2023)
Delay-adaptive Control of Nonlinear Systems with Approximate Neural Operator Predictors
por: Bhan, Luke, et al.
Publicado: (2025)
por: Bhan, Luke, et al.
Publicado: (2025)
Structural System Identification via Validation and Adaptation
por: López, Cristian, et al.
Publicado: (2025)
por: López, Cristian, et al.
Publicado: (2025)
Semi-Gradient SARSA Routing with Theoretical Guarantee on Traffic Stability and Weight Convergence
por: Wu, Yidan, et al.
Publicado: (2025)
por: Wu, Yidan, et al.
Publicado: (2025)
Structure- and Stability-Preserving Learning of Port-Hamiltonian Systems
por: Nguyen, Binh, et al.
Publicado: (2026)
por: Nguyen, Binh, et al.
Publicado: (2026)
Controller Design for Structured State-space Models via Contraction Theory
por: Zakwan, Muhammad, et al.
Publicado: (2026)
por: Zakwan, Muhammad, et al.
Publicado: (2026)
Bilinear Input Modulation for Mamba: Koopman Bilinear Forms for Memory Retention and Multiplicative Computation
por: Fujii, Hiroki, et al.
Publicado: (2026)
por: Fujii, Hiroki, et al.
Publicado: (2026)
Multistability of Self-Attention Dynamics in Transformers
por: Altafini, Claudio
Publicado: (2025)
por: Altafini, Claudio
Publicado: (2025)
Joint Learning of Linear Time-Invariant Dynamical Systems
por: Modi, Aditya, et al.
Publicado: (2021)
por: Modi, Aditya, et al.
Publicado: (2021)
Koopman Kernel Regression
por: Bevanda, Petar, et al.
Publicado: (2023)
por: Bevanda, Petar, et al.
Publicado: (2023)
Ejemplares similares
-
PINNSim: A Simulator for Power System Dynamics based on Physics-Informed Neural Networks
por: Stiasny, Jochen, et al.
Publicado: (2023) -
Correctness Verification of Neural Networks Approximating Differential Equations
por: Ellinas, Petros, et al.
Publicado: (2024) -
Physics-Informed Neural Networks: a Plug and Play Integration into Power System Dynamic Simulations
por: Nadal, Ignasi Ventura, et al.
Publicado: (2024) -
Learning phase-space flows using time-discrete implicit Runge-Kutta PINNs
por: Corral, Álvaro Fernández, et al.
Publicado: (2024) -
Global Performance Guarantees for Neural Network Models of AC Power Flow
por: Chevalier, Samuel, et al.
Publicado: (2022)