Error Bounds for Physics-Informed Neural Networks in Fokker-Planck PDEs
Fuente:
arXiv
Saved in:
| Main Authors: | Kong, Chun-Wei, Laurenti, Luca, McMahon, Jay, Lahijanian, Morteza |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Bayesian Diagnosability and Active Fault Identification
by: Kong, Chun-Wei, et al.
Published: (2025)
by: Kong, Chun-Wei, et al.
Published: (2025)
Training with Hard Constraints: Learning Neural Certificates and Controllers for SDEs
by: Kong, Chun-Wei, et al.
Published: (2026)
by: Kong, Chun-Wei, et al.
Published: (2026)
Time-Varying Reach-Avoid Control Certificates for Stochastic Systems
by: Mazouz, Rayan, et al.
Published: (2026)
by: Mazouz, Rayan, et al.
Published: (2026)
Score-Based Physics-Informed Neural Networks for High-Dimensional Fokker-Planck Equations
by: Hu, Zheyuan, et al.
Published: (2024)
by: Hu, Zheyuan, et al.
Published: (2024)
A Unifying Perspective for Safety of Stochastic Systems: From Barrier Functions to Finite Abstractions
by: Laurenti, Luca, et al.
Published: (2023)
by: Laurenti, Luca, et al.
Published: (2023)
Formal Verification of Unknown Dynamical Systems via Gaussian Process Regression
by: Skovbekk, John, et al.
Published: (2021)
by: Skovbekk, John, et al.
Published: (2021)
Uncertainty Propagation in Stochastic Systems via Mixture Models with Error Quantification
by: Figueiredo, Eduardo, et al.
Published: (2024)
by: Figueiredo, Eduardo, et al.
Published: (2024)
Interval Markov Decision Processes with Continuous Action-Spaces
by: Delimpaltadakis, Giannis, et al.
Published: (2022)
by: Delimpaltadakis, Giannis, et al.
Published: (2022)
AW-EL-PINNs: A Multi-Task Learning Physics-Informed Neural Network for Euler-Lagrange Systems in Optimal Control Problems
by: Li, Chuandong, et al.
Published: (2025)
by: Li, Chuandong, et al.
Published: (2025)
Piecewise Control Barrier Functions for Stochastic Systems
by: Mazouz, Rayan, et al.
Published: (2025)
by: Mazouz, Rayan, et al.
Published: (2025)
PINNSim: A Simulator for Power System Dynamics based on Physics-Informed Neural Networks
by: Stiasny, Jochen, et al.
Published: (2023)
by: Stiasny, Jochen, et al.
Published: (2023)
Promises of Deep Kernel Learning for Control Synthesis
by: Reed, Robert, et al.
Published: (2023)
by: Reed, Robert, et al.
Published: (2023)
CP-PINNs: Data-Driven Changepoints Detection in PDEs Using Online Optimized Physics-Informed Neural Networks
by: Dong, Zhikang, et al.
Published: (2022)
by: Dong, Zhikang, et al.
Published: (2022)
Safety Guarantees for Neural Network Dynamic Systems via Stochastic Barrier Functions
by: Mazouz, Rayan, et al.
Published: (2022)
by: Mazouz, Rayan, et al.
Published: (2022)
Closed-Form Robustness Bounds for Second-Order Pruning of Neural Controller Policies
by: Shamrai, Maksym
Published: (2025)
by: Shamrai, Maksym
Published: (2025)
Competitive Physics Informed Networks
by: Zeng, Qi, et al.
Published: (2022)
by: Zeng, Qi, et al.
Published: (2022)
Data-Driven Strategy Synthesis for Stochastic Systems with Unknown Nonlinear Disturbances
by: Gracia, Ibon, et al.
Published: (2024)
by: Gracia, Ibon, et al.
Published: (2024)
A Priori Error Estimation of Physics-Informed Neural Networks Solving Allen--Cahn and Cahn--Hilliard Equations
by: Zhang, Guangtao, et al.
Published: (2024)
by: Zhang, Guangtao, et al.
Published: (2024)
Error Analysis of Sampling Algorithms for Approximating Stochastic Optimal Control
by: Joshi, Anant A., et al.
Published: (2025)
by: Joshi, Anant A., et al.
Published: (2025)
IntervalMDP.jl: Accelerated Value Iteration for Interval Markov Decision Processes
by: Mathiesen, Frederik Baymler, et al.
Published: (2024)
by: Mathiesen, Frederik Baymler, et al.
Published: (2024)
StochasticBarrier.jl: A Toolbox for Stochastic Barrier Function Synthesis
by: Mazouz, Rayan, et al.
Published: (2026)
by: Mazouz, Rayan, et al.
Published: (2026)
Curvature-Aware Optimization for High-Accuracy Physics-Informed Neural Networks
by: Jnini, Anas, et al.
Published: (2026)
by: Jnini, Anas, et al.
Published: (2026)
Physics-Informed Machine Learning for Characterizing System Stability
by: Koike, Tomoki, et al.
Published: (2025)
by: Koike, Tomoki, et al.
Published: (2025)
Trustworthy Koopman Operator Learning: Invariance Diagnostics and Error Bounds
by: Conradie, Gustav, et al.
Published: (2026)
by: Conradie, Gustav, et al.
Published: (2026)
The Vanishing Gradient Problem for Stiff Neural Differential Equations
by: Fronk, Colby, et al.
Published: (2025)
by: Fronk, Colby, et al.
Published: (2025)
Score-fPINN: Fractional Score-Based Physics-Informed Neural Networks for High-Dimensional Fokker-Planck-Levy Equations
by: Hu, Zheyuan, et al.
Published: (2024)
by: Hu, Zheyuan, et al.
Published: (2024)
Provably Safe Motion Planning Under Unknown Disturbances
by: Gracia, Ibon, et al.
Published: (2026)
by: Gracia, Ibon, et al.
Published: (2026)
Modelling parametric uncertainty in PDEs models via Physics-Informed Neural Networks
by: Panahi, Milad, et al.
Published: (2024)
by: Panahi, Milad, et al.
Published: (2024)
Damping Identification Sensitivity in Flutter Speed Estimation
by: Dessena, Gabriele, et al.
Published: (2025)
by: Dessena, Gabriele, et al.
Published: (2025)
On the Existence of Steady-State Solutions to the Equations Governing Fluid Flow in Networks
by: Srinivasan, Shriram, et al.
Published: (2023)
by: Srinivasan, Shriram, et al.
Published: (2023)
Coverage Explorer: Coverage-guided Test Generation for Cyber Physical Systems
by: Sheikhi, Sanaz, et al.
Published: (2023)
by: Sheikhi, Sanaz, et al.
Published: (2023)
Finding Unknown Unknowns using Cyber-Physical System Simulators (Extended Report)
by: Wehbe, Semaan Douglas, et al.
Published: (2025)
by: Wehbe, Semaan Douglas, et al.
Published: (2025)
All-Pass Fractional OPF: A Solver-Friendly, Physics-Preserving Approximation of AC OPF
by: Hasanzadeh, Milad, et al.
Published: (2026)
by: Hasanzadeh, Milad, et al.
Published: (2026)
Efficiency through Uncertainty: Scalable Formal Synthesis for Stochastic Hybrid Systems
by: Cauchi, Nathalie, et al.
Published: (2019)
by: Cauchi, Nathalie, et al.
Published: (2019)
Temporal Logic Control for Nonlinear Stochastic Systems Under Unknown Disturbances
by: Gracia, Ibon, et al.
Published: (2024)
by: Gracia, Ibon, et al.
Published: (2024)
Efficient Strategy Synthesis for Switched Stochastic Systems with Distributional Uncertainty
by: Gracia, Ibon, et al.
Published: (2022)
by: Gracia, Ibon, et al.
Published: (2022)
Statistical inference of probabilistic origin-destination demand using day-to-day traffic data
by: Ma, Wei, et al.
Published: (2019)
by: Ma, Wei, et al.
Published: (2019)
A Control Framework for CUBESAT Rendezvous and Proximity Operations using Electric Propulsion
by: Lin, Bo-Chuan, et al.
Published: (2024)
by: Lin, Bo-Chuan, et al.
Published: (2024)
A direct optimization algorithm for input-constrained MPC
by: Wu, Liang, et al.
Published: (2023)
by: Wu, Liang, et al.
Published: (2023)
PINNsur: Physics-Informed Neural Networks for PDEs on Curved Surfaces
by: Jain, Pranav, et al.
Published: (2026)
by: Jain, Pranav, et al.
Published: (2026)
Similar Items
-
Bayesian Diagnosability and Active Fault Identification
by: Kong, Chun-Wei, et al.
Published: (2025) -
Training with Hard Constraints: Learning Neural Certificates and Controllers for SDEs
by: Kong, Chun-Wei, et al.
Published: (2026) -
Time-Varying Reach-Avoid Control Certificates for Stochastic Systems
by: Mazouz, Rayan, et al.
Published: (2026) -
Score-Based Physics-Informed Neural Networks for High-Dimensional Fokker-Planck Equations
by: Hu, Zheyuan, et al.
Published: (2024) -
A Unifying Perspective for Safety of Stochastic Systems: From Barrier Functions to Finite Abstractions
by: Laurenti, Luca, et al.
Published: (2023)