Image de couverture de livre

Boundary-Informed Method of Lines for Physics Informed Neural Networks

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Cederholm, Maximilian, Wang, Siyao, Wang, Haochun, Xu, Ruichen, Deng, Yuefan
Format:	Preprint
Publié:	2025
Sujets:	Computational Physics 65N75
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

The Impact of Move Schemes on Simulated Annealing Performance
par: Xu, Ruichen, et autres
Publié: (2025)

Robust Variational Physics-Informed Neural Networks
par: Rojas, Sergio, et autres
Publié: (2023)

Randomized Greedy Algorithms for Neural Network Optimization
par: Xu, Jinchao, et autres
Publié: (2024)

L-HYDRA: Multi-Head Physics-Informed Neural Networks
par: Zou, Zongren, et autres
Publié: (2023)

Deep BSDE Solver on Bounded Domains Part I: General Loss Rate
par: Würschmidt, Maximilian
Publié: (2025)

Walk-on-Interfaces: A Monte Carlo Estimator for an Elliptic Interface Problem with Nonhomogeneous Flux Jump Conditions and a Neumann Boundary Condition
par: Ding, Xinwen, et autres
Publié: (2025)

A posteriori error analysis, Pod-Deim reduced order geometrically parametrized models and unfitted FEMs
par: Karatzas, Efthymios N.
Publié: (2026)

Meshfree Variational Physics Informed Neural Networks (MF-VPINN): an adaptive training strategy
par: Berrone, Stefano, et autres
Publié: (2024)

Active Learning Based Sampling for High-Dimensional Nonlinear Partial Differential Equations
par: Gao, Wenhan, et autres
Publié: (2021)

Computing Black Scholes with Uncertain Volatility-A Machine Learning Approach
par: Hellmuth, Kathrin, et autres
Publié: (2022)

An Eulerian Data Assimilation Method for Two-Layer Quasi-Geostrophic Model in Physical Domain
par: Yun, Hyeonggeun, et autres
Publié: (2025)

A probabilistic approach to spectral analysis of Cauchy-type inverse problems: Convergence and stability analysis
par: Cîmpean, Iulian, et autres
Publié: (2025)

A posteriori analysis of neural network approximations
par: Führer, Thomas, et autres
Publié: (2025)

Weak Adversarial Neural Pushforward Method for the Wigner Transport Equation
par: He, Andrew Qing, et autres
Publié: (2026)

Numerical spectral analysis of Cauchy-type inverse problems: A probabilistic approach
par: Cîmpean, Iulian, et autres
Publié: (2024)

Solving Schrödinger Equation Using Tensor Neural Network
par: Liao, Yangfei, et autres
Publié: (2022)

Kolmogorov-Arnold Representation for Symplectic Learning: Advancing Hamiltonian Neural Networks
par: Wu, Zongyu, et autres
Publié: (2025)

An analysis of the derivative-free loss method for solving PDEs
par: Han, Jihun, et autres
Publié: (2023)

Adaptive Neural Network Subspace Method for Solving Partial Differential Equations with High Accuracy
par: Lin, Zhongshuo, et autres
Publié: (2024)

Regularization effect of noise on fully discrete approximation for stochastic reaction-diffusion equation near sharp interface limit
par: Cui, Jianbo
Publié: (2023)

Fast operator learning for mapping correlations
par: Khoo, Yuehaw, et autres
Publié: (2025)

Velocity-Inferred Hamiltonian Neural Networks: Learning Energy-Conserving Dynamics from Position-Only Data
par: Xu, Ruichen, et autres
Publié: (2025)

Stabilized Lagrange Multipliers for Dirichlet Boundary Conditions in Divergence Preserving Unfitted Methods
par: Frachon, Thomas, et autres
Publié: (2024)

Non-Conforming Finite Element Method For Constrained Dirichlet Boundary Control Problem
par: Chowdhury, Sudipto, et autres
Publié: (2024)

Learning Neural Pushforward Samplers for Distributions from Fokker-Planck Equations by Weak Adversarial Training
par: He, Andrew Qing, et autres
Publié: (2025)

The Numerical Solution of the External Dirichlet Generalized Harmonic Problem for a Sphere by the Method of Probabilistic Solution
par: Zakradze, Mamuli, et autres
Publié: (2024)

Neural Network Dual Norms for Minimal Residual Finite Element Methods
par: Alsobhi, Hamd, et autres
Publié: (2025)

Non-Asymptotic Analysis of Projected Gradient Descent for Physics-Informed Neural Networks
par: Nießen, Jonas, et autres
Publié: (2025)

Instability of Numerical Method for Micromagnetics Simulations with Large Damping Parameters
par: Xie, Changjian, et autres
Publié: (2025)

Simplified Weak Galerkin Methods for Linear Elasticity on Nonconvex Domains
par: Wang, Chunmei, et autres
Publié: (2024)

Weak Adversarial Neural Pushforward Method for the McKean-Vlasov / Mean-Field Fokker-Planck Equation
par: He, Andrew Qing, et autres
Publié: (2026)

Auto-Stabilized Weak Galerkin Finite Element Methods on Polytopal Meshes without Convexity Constraints
par: Wang, Chunmei
Publié: (2024)

Simplified Weak Galerkin Finite Element Methods for Biharmonic Equations on Non-Convex Polytopal Meshes
par: Wang, Chunmei
Publié: (2024)

Neural Pushforward Samplers for the Fokker-Planck Equation on Embedded Riemannian Manifolds
par: He, Andrew Qing, et autres
Publié: (2026)

Auto-Stabilized Weak Galerkin Finite Element Methods for Biharmonic Equations on Polytopal Meshes without Convexity Assumptions
par: Wang, Chunmei
Publié: (2024)

Enhancing Micromagnetics Simulations with a Third-Order Semi-Implicit Projection Method
par: Xie, Changjian, et autres
Publié: (2025)

A two-grid Adaptive Finite Element Method for the Dirichlet Boundary Control Problem Governed by Stokes Equation
par: Gudi, Thirupathi, et autres
Publié: (2024)

A Simple and Robust Weak Galerkin Method for the Brinkman Equations on Non-Convex Polytopal Meshes
par: Wang, Chunmei, et autres
Publié: (2025)

Auto-Stabilized Weak Galerkin Finite Element Methods for Stokes Equations on Non-Convex Polytopal Meshes
par: Wang, Chunmei, et autres
Publié: (2025)

A Simple Weak Galerkin Finite Element Method for the Reissner-Mindlin Plate Model on Non-Convex Polytopal Meshes
par: Wang, Chunmei, et autres
Publié: (2025)