Copertina

The Neural Network Approach to Inverse Problems in Differential Equations

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Xu, Kailai, Darve, Eric
Natura:	Preprint
Pubblicazione:	2019
Soggetti:	Numerical Analysis
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Necessary and Sufficient Conditions for the Existence of an LU Factorization for General Rank Deficient Matrices
di: Darve, Eric
Pubblicazione: (2026)

Data-Guided Physics-Informed Neural Networks for Solving Inverse Problems in Partial Differential Equations
di: Zhou, Wei, et al.
Pubblicazione: (2024)

A numerically stable communication-avoiding s-step GMRES algorithm
di: Xu, Zan, et al.
Pubblicazione: (2023)

On the Non-Linear Integral Equation Approach for an Inverse Boundary Value Problem for the Heat Equation
di: Chapko, Roman, et al.
Pubblicazione: (2019)

Orthogonal Constrained Neural Networks for Solving Structured Inverse Eigenvalue Problems
di: Zhang, Shuai, et al.
Pubblicazione: (2024)

PhysicsSolver: Transformer-Enhanced Physics-Informed Neural Networks for Forward and Forecasting Problems in Partial Differential Equations
di: Zhu, Zhenyi, et al.
Pubblicazione: (2025)

Variational Inverting Network for Statistical Inverse Problems of Partial Differential Equations
di: Jia, Junxiong, et al.
Pubblicazione: (2022)

Solving Partial Differential Equations Using Artificial Neural Networks
di: Uriarte, Carlos
Pubblicazione: (2024)

A Neural Latent Dynamics Approach for Solving Inverse Problems in Cardiac Electrophysiology
di: Centofanti, Edoardo, et al.
Pubblicazione: (2026)

Novel Product Manifold Modeling and Orthogonality-Constrained Neural Network Solver for Parameterized Generalized Inverse Eigenvalue Problems
di: Zhang, Shuai, et al.
Pubblicazione: (2026)

Bi-fidelity Interpolative Decomposition for Multimodal Data
di: Cutforth, Murray, et al.
Pubblicazione: (2025)

Generalized Transferable Neural Networks for Steady-State Partial Differential Equations
di: Cheng, Tao, et al.
Pubblicazione: (2026)

Encoded Forward Backward Stochastic Neural Network for High-Dimensional Backward Stochastic Differential Equations and Parabolic Partial Differential Equations
di: Zhang, Zhao, et al.
Pubblicazione: (2026)

Physics-embedded Fourier Neural Network for Partial Differential Equations
di: Xu, Qingsong, et al.
Pubblicazione: (2024)

Energy-Equidistributed Moving Sampling Physics-informed Neural Networks for Solving Conservative Partial Differential Equations
di: Gao, Qinjiao, et al.
Pubblicazione: (2025)

ODE-DPS: ODE-based Diffusion Posterior Sampling for Inverse Problems in Partial Differential Equation
di: Jiang, Enze, et al.
Pubblicazione: (2024)

Observations on Recurrent Loss in the Neural Network Model of a Partial Differential Equation: the Advection-Diffusion Equation
di: Reeger, Jonah A.
Pubblicazione: (2025)

A Priori Estimation of the Approximation, Optimization and Generalization Errors of Random Neural Networks for Solving Partial Differential Equations
di: Xu, Xianliang, et al.
Pubblicazione: (2024)

Automatic Differentiation is Essential in Training Neural Networks for Solving Differential Equations
di: Chen, Chuqi, et al.
Pubblicazione: (2024)

A Gaussian Process Framework for Solving Forward and Inverse Problems Involving Nonlinear Partial Differential Equations
di: Mora, Carlos, et al.
Pubblicazione: (2024)

Inverse Random Source Problem for the Helmholtz Equation from Statistical Phaseless Data
di: Chen, Qiao-Ping, et al.
Pubblicazione: (2025)

Physics-informed Multiresolution Wavelet Neural Network Method for Solving Partial Differential Equations
di: Han, Feng, et al.
Pubblicazione: (2025)

Least-Squares Neural Network (LSNN) Method for Scalar Hyperbolic Partial Differential Equations
di: Liu, Min, et al.
Pubblicazione: (2026)

Regularity-Conforming Neural Networks (ReCoNNs) for solving Partial Differential Equations
di: Taylor, Jamie M., et al.
Pubblicazione: (2024)

A Unified Benchmark of Physics-Informed Neural Networks and Kolmogorov-Arnold Networks for Ordinary and Partial Differential Equations
di: Dzimah, Salvador K., et al.
Pubblicazione: (2026)

Adaptive Basis-inspired Deep Neural Network for Solving Partial Differential Equations with Localized Features
di: Li, Ke, et al.
Pubblicazione: (2024)

Domain Decomposition Subspace Neural Network Method for Solving Linear and Nonlinear Partial Differential Equations
di: Fu, Zhenxing, et al.
Pubblicazione: (2025)

Scalable Mechanistic Neural Networks for Differential Equations and Machine Learning
di: Chen, Jiale, et al.
Pubblicazione: (2024)

Convexification for a Coefficient Inverse Problem for a System of Two Coupled Nonlinear Parabolic Equations
di: Klibanov, Michael V., et al.
Pubblicazione: (2024)

Fine-Tuning DeepONets to Enhance Physics-informed Neural Networks for solving Partial Differential Equations
di: Wu, Sidi
Pubblicazione: (2024)

Structure-Preserving Neural Ordinary Differential Equations for Stiff Systems
di: Loya, Allen Alvarez, et al.
Pubblicazione: (2025)

Solving the Wide-band Inverse Scattering Problem via Equivariant Neural Networks
di: Zhang, Borong, et al.
Pubblicazione: (2022)

Randomized Neural Networks for Partial Differential Equation on Static and Evolving Surfaces
di: Sun, Jingbo, et al.
Pubblicazione: (2026)

Random Neural Network Expressivity for Non-Linear Partial Differential Equations
di: Mehmood, Muhammed Ali, et al.
Pubblicazione: (2026)

Randomized Neural Networks for Integro-Differential Equations with Application to Neutron Transport
di: Dang, Haoning, et al.
Pubblicazione: (2026)

Solving Inverse Acoustic Obstacle Scattering Problem with Phaseless Far-Field Measurement Using Deep Neural Network Surrogates
di: Fan, Yuxin, et al.
Pubblicazione: (2025)

Graph Neural Regularizers for PDE Inverse Problems
di: Lauga, William, et al.
Pubblicazione: (2025)

A Kolmogorov High Order Deep Neural Network for High Frequency Partial Differential Equations in High Dimensions
di: Zhang, Yaqin, et al.
Pubblicazione: (2025)

Dual Variational Neural Network for the $p$-Laplace Problem
di: Hu, Tianhao, et al.
Pubblicazione: (2026)

Solving Forward and Inverse Problems of Contact Mechanics using Physics-Informed Neural Networks
di: Sahin, T., et al.
Pubblicazione: (2023)