Image de couverture de livre

Efficient Numerical Wave Propagation Enhanced By An End-to-End Deep Learning Model

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Kaiser, Luis, Tsai, Richard, Klingenberg, Christian
Format:	Preprint
Publié:	2024
Sujets:	Analysis of PDEs Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Deep Learning-Enhanced Calibration of the Heston Model: A Unified Framework
par: Zadgar, Arman, et autres
Publié: (2025)

Singularity Formation: Synergy in Theoretical, Numerical and Machine Learning Approaches
par: Wang, Yixuan
Publié: (2026)

DeepRitzSplit Neural Operator for Phase-Field Models via Energy Splitting
par: Huang, Chih-Kang, et autres
Publié: (2026)

Neural Sampling from Boltzmann Densities: Fisher-Rao Curves in the Wasserstein Geometry
par: Chemseddine, Jannis, et autres
Publié: (2024)

Mathematical Modeling of Cancer-Bacterial Therapy: Analysis and Numerical Simulation via Physics-Informed Neural Networks
par: Farkane, Ayoub, et autres
Publié: (2026)

BGK model for rarefied gas in a bounded domain
par: Chen, Hongxu, et autres
Publié: (2025)

Numerical Schemes for Signature Kernels
par: Cass, Thomas, et autres
Publié: (2025)

Adapting Noise to Data: Generative Flows from 1D Processes
par: Chemseddine, Jannis, et autres
Publié: (2025)

Partial Differential Equations in the Age of Machine Learning: A Critical Synthesis of Classical, Machine Learning, and Hybrid Methods
par: Nooraiepour, Mohammad, et autres
Publié: (2026)

Is Zero-Shot Super-Resolution Possible in Operator Learning?
par: Subedi, Unique, et autres
Publié: (2026)

Stiff Transfer Learning for Physics-Informed Neural Networks
par: Seiler, Emilien, et autres
Publié: (2025)

An End-to-End Deep Learning Method for Solving Nonlocal Allen-Cahn and Cahn-Hilliard Phase-Field Models
par: Geng, Yuwei, et autres
Publié: (2024)

Mean-Field Analysis for Learning Subspace-Sparse Polynomials with Gaussian Input
par: Chen, Ziang, et autres
Publié: (2024)

Learning functional components of PDEs from data using neural networks
par: Loman, Torkel E., et autres
Publié: (2026)

Generalization Error Bounds for Picard-Type Operator Learning in Nonlinear Parabolic PDEs
par: Taniguchi, Koichi, et autres
Publié: (2026)

Learning PDE Solvers with Physics and Data: A Unifying View of Physics-Informed Neural Networks and Neural Operators
par: Dai, Yilong, et autres
Publié: (2026)

Global Well-posedness and Convergence Analysis of Score-based Generative Models via Sharp Lipschitz Estimates
par: Mooney, Connor, et autres
Publié: (2024)

Artifacts of Numerical Integration in Learning Dynamical Systems
par: Lu, Bing-Ze, et autres
Publié: (2025)

Soliton profiles: Classical Numerical Schemes vs. Neural Network - Based Solvers
par: Haight, Chandler, et autres
Publié: (2025)

Size Lowerbounds for Deep Operator Networks
par: Mukherjee, Anirbit, et autres
Publié: (2023)

Propagation of Chaos in Contextual Flow Maps
par: Chen, Shi, et autres
Publié: (2026)

Interaction-Force Transport Gradient Flows
par: Gladin, Egor, et autres
Publié: (2024)

Nonlocal Attention Operator: Materializing Hidden Knowledge Towards Interpretable Physics Discovery
par: Yu, Yue, et autres
Publié: (2024)

On Probabilistic Embeddings in Optimal Dimension Reduction
par: Murray, Ryan, et autres
Publié: (2024)

Improved Graph-based semi-supervised learning Schemes
par: Bozorgnia, Farid
Publié: (2024)

Solving the Poisson Equation with Dirichlet data by shallow ReLU$^α$-networks: A regularity and approximation perspective
par: Vaishampayan, Malhar, et autres
Publié: (2024)

Kernel Approximation of Fisher-Rao Gradient Flows
par: Zhu, Jia-Jie, et autres
Publié: (2024)

A Physics Informed Neural Network (PINN) Methodology for Coupled Moving Boundary PDEs
par: Kathane, Shivprasad, et autres
Publié: (2024)

Minimax Rates for the Estimation of Eigenpairs of Weighted Laplace-Beltrami Operators on Manifolds
par: Trillos, Nicolás García, et autres
Publié: (2025)

The emergence of clusters in self-attention dynamics
par: Geshkovski, Borjan, et autres
Publié: (2023)

Double Coupling Architecture and Training Method for Optimization Problems of Differential Algebraic Equations with Parameters
par: Yang, Wenqiang, et autres
Publié: (2026)

Trace Regularity PINNs: Enforcing $\mathrm{H}^{\frac{1}{2}}(\partial Ω)$ for Boundary Data
par: Kim, Doyoon, et autres
Publié: (2025)

Regularity of Solutions to Beckmann's Parametric Optimal Transport
par: Gottschalk, Hanno, et autres
Publié: (2026)

Full Field Inversion of the Attenuated Wave Equation: Theory and Numerical Inversion
par: Do, Ngoc, et autres
Publié: (2024)

Propagation of Wave Packets Close to Conical Intersections
par: Curely, Marianne
Publié: (2025)

End-to-End Mesh Optimization of a Hybrid Deep Learning Black-Box PDE Solver
par: Ma, Shaocong, et autres
Publié: (2024)

Wasserstein Bounds for generative diffusion models with Gaussian tail targets
par: Wang, Xixian, et autres
Publié: (2024)

Barron Space Representations for Elliptic PDEs with Homogeneous Boundary Conditions
par: Chen, Ziang, et autres
Publié: (2025)

Generalization Bounds for Physics-Informed Neural Networks for the Incompressible Navier-Stokes Equations
par: Andre-Sloan, Sebastien, et autres
Publié: (2026)

Unified generalization analysis for physics informed neural networks
par: Hashimoto, Yuka, et autres
Publié: (2026)