Copertina

EGPT-PINN: Entropy-enhanced Generative Pre-Trained Physics Informed Neural Networks for parameterized nonlinear conservation laws

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Ji, Yajie, Chen, Yanlai, Xu, Zhenli
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Numerical Analysis 65M25, 65M70, 68T07
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Neural Entropy-stable conservative flux form neural networks for learning hyperbolic conservation laws
di: Liu, Lizuo, et al.
Pubblicazione: (2025)

S$^2$GPT-PINNs: Sparse and Small models for PDEs
di: Ji, Yajie, et al.
Pubblicazione: (2025)

Entropy stable conservative flux form neural networks
di: Liu, Lizuo, et al.
Pubblicazione: (2024)

Solving the BGK Model and Boltzmann equation by Fourier Neural Operator with conservative constraints
di: Hu, Boyun, et al.
Pubblicazione: (2025)

Physics-Informed Neural Networks: Bridging the Divide Between Conservative and Non-Conservative Equations
di: Neelan, Arun Govind, et al.
Pubblicazione: (2025)

Neural Network Element Method for Partial Differential Equations
di: Wang, Yifan, et al.
Pubblicazione: (2025)

A neural network method for scalar conservation laws with convergence rates for shock-wave solutions
di: Cao, Jiachuan, et al.
Pubblicazione: (2026)

On the robustness of high-order upwind summation-by-parts methods for nonlinear conservation laws
di: Ranocha, Hendrik, et al.
Pubblicazione: (2023)

Solving High Dimensional Partial Differential Equations Using Tensor Neural Network and A Posteriori Error Estimators
di: Wang, Yifan, et al.
Pubblicazione: (2023)

Parametric Hyperbolic Conservation Laws: A Unified Framework for Conservation, Entropy Stability, and Hyperbolicity
di: Liu, Lizuo, et al.
Pubblicazione: (2026)

Neural semi-Lagrangian method for high-dimensional advection-diffusion problems
di: Franck, Emmanuel, et al.
Pubblicazione: (2025)

Learning WENO for entropy stable schemes to solve conservation laws
di: Charles, Philip, et al.
Pubblicazione: (2024)

Recurrent Neural Operators: Stable Long-Term PDE Prediction
di: Ye, Zaijun, et al.
Pubblicazione: (2025)

Physics-Informed Neural Networks: A Didactic Derivation of the Complete Training Cycle
di: Tahimi, Abdeladhim
Pubblicazione: (2026)

Maximum principle preserving time implicit DGSEM for nonlinear scalar conservation laws
di: Renac, Florent
Pubblicazione: (2024)

FastLRNR and Sparse Physics Informed Backpropagation
di: Cho, Woojin, et al.
Pubblicazione: (2024)

All Equalities Are Equal, but Some Are More Equal Than Others: The Effect of Implementation Aliasing on the Numerical Solution to Conservation Equations
di: Trojak, Will, et al.
Pubblicazione: (2019)

Summation-by-parts operators for general function spaces: The second derivative
di: Glaubitz, Jan, et al.
Pubblicazione: (2023)

Generalized upwind summation-by-parts operators and their application to nodal discontinuous Galerkin methods
di: Glaubitz, Jan, et al.
Pubblicazione: (2024)

Two-scale integrators with high accuracy and long-time conservations for the nonlinear Klein-Gordon equation in the nonrelativistic limit regime
di: Wang, Bin, et al.
Pubblicazione: (2022)

Data-Driven Discovery of Sign-Indefinite Artificial Viscosity for Linear Convection -- A Space-Time Reconvolution Perspective
di: Neelan, Arun Govind
Pubblicazione: (2026)

Prediction of discretization of online GMsFEM using deep learning for Richards equation
di: Spiridonov, Denis, et al.
Pubblicazione: (2024)

Coupling-Robust Accuracy in Multiphysics Physics Informed Neural Networks via Kronecker-Preconditioned Optimization
di: Park, Youngjae, et al.
Pubblicazione: (2026)

High-order mass- and energy-conserving methods for the nonlinear Schrödinger equation and its hyperbolization
di: Ranocha, Hendrik, et al.
Pubblicazione: (2025)

A Theory-guided Weighted $L^2$ Loss for solving the BGK model via Physics-informed neural networks
di: Ko, Gyounghun, et al.
Pubblicazione: (2026)

Learning Low Rank Neural Representations of Hyperbolic Wave Dynamics from Data
di: Cho, Woojin, et al.
Pubblicazione: (2025)

GoRINNs: Godunov-Riemann Informed Neural Networks for Learning Hyperbolic Conservation Laws
di: Patsatzis, Dimitrios G., et al.
Pubblicazione: (2024)

Invariant domain preserving limiting of time explicit and time implicit discretizations for systems of conservation laws
di: Fanizza, Bartolomeo, et al.
Pubblicazione: (2026)

Local cubic spline interpolation for Vlasov-type equations on a multi-patch geometry
di: Vidal, Pauline, et al.
Pubblicazione: (2025)

Data-Free Asymptotics-Informed Operator Networks for Singularly Perturbed PDEs
di: Lee, Jinsil, et al.
Pubblicazione: (2025)

Learn and Verify: A Framework for Rigorous Verification of Physics-Informed Neural Networks
di: Tanaka, Kazuaki, et al.
Pubblicazione: (2026)

Convergent Operator-Splitting Scheme for Viscosity Solutions: A Foundation for Learning Domain-to-Solution Maps
di: Wu, Po-Yi
Pubblicazione: (2025)

An optimization-based construction procedure for function space based summation-by-parts operators on arbitrary grids
di: Glaubitz, Jan, et al.
Pubblicazione: (2024)

Neural enrichment finite element method: A hybrid framework for problems with strong oscillations or interface problems
di: Guo, Shihan, et al.
Pubblicazione: (2026)

PACMANN: Point Adaptive Collocation Method for Artificial Neural Networks
di: Visser, Coen, et al.
Pubblicazione: (2024)

Space-time parallel scaling of Parareal with a physics-informed Fourier Neural Operator coarse propagator applied to the Black-Scholes equation
di: Ibrahim, Abdul Qadir, et al.
Pubblicazione: (2024)

Error bounds for Physics Informed Neural Networks in Nonlinear Schrödinger equations placed on unbounded domains
di: Alejo, Miguel Á., et al.
Pubblicazione: (2024)

Development and Analysis of Chien-Physics-Informed Neural Networks for Singular Perturbation Problems
di: Singh, Gautam, et al.
Pubblicazione: (2025)

Solving nonlinear Klein-Gordon equation with non-smooth solution by a geometric low-regularity integrator
di: Wang, Bin, et al.
Pubblicazione: (2023)

Error estimates of fully semi-Lagrangian schemes for diffusive conservation laws
di: Takemura, Haruki
Pubblicazione: (2025)