:: Library Catalog

Image de couverture de livre

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Cheng, Tao, Ju, Lili, Qiao, Zhonghua, Zhang, Xiaoping
Format:	Preprint
Publié:	2026
Sujets:	Numerical Analysis
Accès en ligne:	https://arxiv.org/abs/2604.03020
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

A Structure-Preserving Framework for Solving Parabolic Partial Differential Equations with Neural Networks
par: Chen, Gaohang, et autres
Publié: (2025)

Reduced Basis Methods for Parametric Steady-State Radiative Transfer Equation
par: Matsuda, Kimberly, et autres
Publié: (2025)

Solving Partial Differential Equations Using Artificial Neural Networks
par: Uriarte, Carlos
Publié: (2024)

Encoded Forward Backward Stochastic Neural Network for High-Dimensional Backward Stochastic Differential Equations and Parabolic Partial Differential Equations
par: Zhang, Zhao, et autres
Publié: (2026)

A Multiple Transferable Neural Network Method with Domain Decomposition for Elliptic Interface Problems
par: Lu, Tianzheng, et autres
Publié: (2025)

Physics-embedded Fourier Neural Network for Partial Differential Equations
par: Xu, Qingsong, et autres
Publié: (2024)

Adaptive Basis-inspired Deep Neural Network for Solving Partial Differential Equations with Localized Features
par: Li, Ke, et autres
Publié: (2024)

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

Least-Squares Neural Network (LSNN) Method for Scalar Hyperbolic Partial Differential Equations
par: Liu, Min, et autres
Publié: (2026)

Physics-informed Multiresolution Wavelet Neural Network Method for Solving Partial Differential Equations
par: Han, Feng, et autres
Publié: (2025)

Regularity-Conforming Neural Networks (ReCoNNs) for solving Partial Differential Equations
par: Taylor, Jamie M., et autres
Publié: (2024)

A Priori Estimation of the Approximation, Optimization and Generalization Errors of Random Neural Networks for Solving Partial Differential Equations
par: Xu, Xianliang, et autres
Publié: (2024)

Energy-Equidistributed Moving Sampling Physics-informed Neural Networks for Solving Conservative Partial Differential Equations
par: Gao, Qinjiao, et autres
Publié: (2025)

Randomized Neural Networks for Partial Differential Equation on Static and Evolving Surfaces
par: Sun, Jingbo, et autres
Publié: (2026)

Random Neural Network Expressivity for Non-Linear Partial Differential Equations
par: Mehmood, Muhammed Ali, et autres
Publié: (2026)

Domain Decomposition Subspace Neural Network Method for Solving Linear and Nonlinear Partial Differential Equations
par: Fu, Zhenxing, et autres
Publié: (2025)

Reduced Krylov Basis Methods for Parametric Partial Differential Equations
par: Li, Yuwen, et autres
Publié: (2024)

An Unconstrained Formulation of Some Constrained Partial Differential Equations and its Application to Finite Neuron Methods
par: Jia, Jiwei, et autres
Publié: (2024)

An Inexact Low-Rank Source Iteration for Steady-State Radiative Transfer Equation with Diffusion Synthetic Acceleration
par: Guo, Wei, et autres
Publié: (2025)

A Kolmogorov High Order Deep Neural Network for High Frequency Partial Differential Equations in High Dimensions
par: Zhang, Yaqin, et autres
Publié: (2025)

Chebyshev Spectral Neural Networks for Solving Partial Differential Equations
par: Yin, Pengsong, et autres
Publié: (2024)

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

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

On the Existence of Steady-State Solutions to the Equations Governing Fluid Flow in Networks
par: Srinivasan, Shriram, et autres
Publié: (2023)

An Unsupervised Network Architecture Search Method for Solving Partial Differential Equations
par: Li, Qing, et autres
Publié: (2025)

PhysicsSolver: Transformer-Enhanced Physics-Informed Neural Networks for Forward and Forecasting Problems in Partial Differential Equations
par: Zhu, Zhenyi, et autres
Publié: (2025)

Two-scale Neural Networks for Partial Differential Equations with Small Parameters
par: Zhuang, Qiao, et autres
Publié: (2024)

Generalization Limits of In-Context Operator Networks for Higher-Order Partial Differential Equations
par: Mahowald, Jamie, et autres
Publié: (2026)

HAMLET: Graph Transformer Neural Operator for Partial Differential Equations
par: Bryutkin, Andrey, et autres
Publié: (2024)

Pseudo-Differential Neural Operator: Generalized Fourier Neural Operator for Learning Solution Operators of Partial Differential Equations
par: Shin, Jin Young, et autres
Publié: (2022)

Causal Operator Discovery in Partial Differential Equations via Counterfactual Physics-Informed Neural Networks
par: Katende, Ronald
Publié: (2025)

Data-Guided Physics-Informed Neural Networks for Solving Inverse Problems in Partial Differential Equations
par: Zhou, Wei, et autres
Publié: (2024)

Inverse Evolution Layers: Physics-informed Regularizers for Deep Neural Networks
par: Liu, Chaoyu, et autres
Publié: (2023)

Hierarchical Network Partitioning for Solution of Potential-Driven, Steady-State Nonlinear Network Flow Equations
par: Srinivasan, Shriram, et autres
Publié: (2024)

Deep Parallel Spectral Neural Operators for Solving Partial Differential Equations with Enhanced Low-Frequency Learning Capability
par: Ma, Qinglong, et autres
Publié: (2024)

The Neural Network Approach to Inverse Problems in Differential Equations
par: Xu, Kailai, et autres
Publié: (2019)

Deep Finite Volume Method for Partial Differential Equations
par: Cen, Jianhuan, et autres
Publié: (2023)

General-Kindred Physics-Informed Neural Network to the Solutions of Singularly Perturbed Differential Equations
par: Wang, Sen, et autres
Publié: (2024)

Quantum Recurrent Neural Networks with Encoder-Decoder for Time-Dependent Partial Differential Equations
par: Chen, Yuan, et autres
Publié: (2025)

Global-in-time energy stability analysis for the exponential time differencing Runge-Kutta scheme for the phase field crystal equation
par: Li, Xiao, et autres
Publié: (2024)