Saved in:
| Main Authors: | Cheng, Tao, Ju, Lili, Qiao, Zhonghua, Zhang, Xiaoping |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2604.03020 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
A Structure-Preserving Framework for Solving Parabolic Partial Differential Equations with Neural Networks
by: Chen, Gaohang, et al.
Published: (2025)
by: Chen, Gaohang, et al.
Published: (2025)
Reduced Basis Methods for Parametric Steady-State Radiative Transfer Equation
by: Matsuda, Kimberly, et al.
Published: (2025)
by: Matsuda, Kimberly, et al.
Published: (2025)
Solving Partial Differential Equations Using Artificial Neural Networks
by: Uriarte, Carlos
Published: (2024)
by: Uriarte, Carlos
Published: (2024)
Encoded Forward Backward Stochastic Neural Network for High-Dimensional Backward Stochastic Differential Equations and Parabolic Partial Differential Equations
by: Zhang, Zhao, et al.
Published: (2026)
by: Zhang, Zhao, et al.
Published: (2026)
A Multiple Transferable Neural Network Method with Domain Decomposition for Elliptic Interface Problems
by: Lu, Tianzheng, et al.
Published: (2025)
by: Lu, Tianzheng, et al.
Published: (2025)
Physics-embedded Fourier Neural Network for Partial Differential Equations
by: Xu, Qingsong, et al.
Published: (2024)
by: Xu, Qingsong, et al.
Published: (2024)
Adaptive Basis-inspired Deep Neural Network for Solving Partial Differential Equations with Localized Features
by: Li, Ke, et al.
Published: (2024)
by: Li, Ke, et al.
Published: (2024)
Observations on Recurrent Loss in the Neural Network Model of a Partial Differential Equation: the Advection-Diffusion Equation
by: Reeger, Jonah A.
Published: (2025)
by: Reeger, Jonah A.
Published: (2025)
Least-Squares Neural Network (LSNN) Method for Scalar Hyperbolic Partial Differential Equations
by: Liu, Min, et al.
Published: (2026)
by: Liu, Min, et al.
Published: (2026)
Physics-informed Multiresolution Wavelet Neural Network Method for Solving Partial Differential Equations
by: Han, Feng, et al.
Published: (2025)
by: Han, Feng, et al.
Published: (2025)
Regularity-Conforming Neural Networks (ReCoNNs) for solving Partial Differential Equations
by: Taylor, Jamie M., et al.
Published: (2024)
by: Taylor, Jamie M., et al.
Published: (2024)
A Priori Estimation of the Approximation, Optimization and Generalization Errors of Random Neural Networks for Solving Partial Differential Equations
by: Xu, Xianliang, et al.
Published: (2024)
by: Xu, Xianliang, et al.
Published: (2024)
Energy-Equidistributed Moving Sampling Physics-informed Neural Networks for Solving Conservative Partial Differential Equations
by: Gao, Qinjiao, et al.
Published: (2025)
by: Gao, Qinjiao, et al.
Published: (2025)
Randomized Neural Networks for Partial Differential Equation on Static and Evolving Surfaces
by: Sun, Jingbo, et al.
Published: (2026)
by: Sun, Jingbo, et al.
Published: (2026)
Random Neural Network Expressivity for Non-Linear Partial Differential Equations
by: Mehmood, Muhammed Ali, et al.
Published: (2026)
by: Mehmood, Muhammed Ali, et al.
Published: (2026)
Domain Decomposition Subspace Neural Network Method for Solving Linear and Nonlinear Partial Differential Equations
by: Fu, Zhenxing, et al.
Published: (2025)
by: Fu, Zhenxing, et al.
Published: (2025)
Reduced Krylov Basis Methods for Parametric Partial Differential Equations
by: Li, Yuwen, et al.
Published: (2024)
by: Li, Yuwen, et al.
Published: (2024)
An Unconstrained Formulation of Some Constrained Partial Differential Equations and its Application to Finite Neuron Methods
by: Jia, Jiwei, et al.
Published: (2024)
by: Jia, Jiwei, et al.
Published: (2024)
An Inexact Low-Rank Source Iteration for Steady-State Radiative Transfer Equation with Diffusion Synthetic Acceleration
by: Guo, Wei, et al.
Published: (2025)
by: Guo, Wei, et al.
Published: (2025)
A Kolmogorov High Order Deep Neural Network for High Frequency Partial Differential Equations in High Dimensions
by: Zhang, Yaqin, et al.
Published: (2025)
by: Zhang, Yaqin, et al.
Published: (2025)
Chebyshev Spectral Neural Networks for Solving Partial Differential Equations
by: Yin, Pengsong, et al.
Published: (2024)
by: Yin, Pengsong, et al.
Published: (2024)
A Unified Benchmark of Physics-Informed Neural Networks and Kolmogorov-Arnold Networks for Ordinary and Partial Differential Equations
by: Dzimah, Salvador K., et al.
Published: (2026)
by: Dzimah, Salvador K., et al.
Published: (2026)
Fine-Tuning DeepONets to Enhance Physics-informed Neural Networks for solving Partial Differential Equations
by: Wu, Sidi
Published: (2024)
by: Wu, Sidi
Published: (2024)
On the Existence of Steady-State Solutions to the Equations Governing Fluid Flow in Networks
by: Srinivasan, Shriram, et al.
Published: (2023)
by: Srinivasan, Shriram, et al.
Published: (2023)
An Unsupervised Network Architecture Search Method for Solving Partial Differential Equations
by: Li, Qing, et al.
Published: (2025)
by: Li, Qing, et al.
Published: (2025)
PhysicsSolver: Transformer-Enhanced Physics-Informed Neural Networks for Forward and Forecasting Problems in Partial Differential Equations
by: Zhu, Zhenyi, et al.
Published: (2025)
by: Zhu, Zhenyi, et al.
Published: (2025)
Two-scale Neural Networks for Partial Differential Equations with Small Parameters
by: Zhuang, Qiao, et al.
Published: (2024)
by: Zhuang, Qiao, et al.
Published: (2024)
Generalization Limits of In-Context Operator Networks for Higher-Order Partial Differential Equations
by: Mahowald, Jamie, et al.
Published: (2026)
by: Mahowald, Jamie, et al.
Published: (2026)
HAMLET: Graph Transformer Neural Operator for Partial Differential Equations
by: Bryutkin, Andrey, et al.
Published: (2024)
by: Bryutkin, Andrey, et al.
Published: (2024)
Pseudo-Differential Neural Operator: Generalized Fourier Neural Operator for Learning Solution Operators of Partial Differential Equations
by: Shin, Jin Young, et al.
Published: (2022)
by: Shin, Jin Young, et al.
Published: (2022)
Causal Operator Discovery in Partial Differential Equations via Counterfactual Physics-Informed Neural Networks
by: Katende, Ronald
Published: (2025)
by: Katende, Ronald
Published: (2025)
Data-Guided Physics-Informed Neural Networks for Solving Inverse Problems in Partial Differential Equations
by: Zhou, Wei, et al.
Published: (2024)
by: Zhou, Wei, et al.
Published: (2024)
Inverse Evolution Layers: Physics-informed Regularizers for Deep Neural Networks
by: Liu, Chaoyu, et al.
Published: (2023)
by: Liu, Chaoyu, et al.
Published: (2023)
Hierarchical Network Partitioning for Solution of Potential-Driven, Steady-State Nonlinear Network Flow Equations
by: Srinivasan, Shriram, et al.
Published: (2024)
by: Srinivasan, Shriram, et al.
Published: (2024)
Deep Parallel Spectral Neural Operators for Solving Partial Differential Equations with Enhanced Low-Frequency Learning Capability
by: Ma, Qinglong, et al.
Published: (2024)
by: Ma, Qinglong, et al.
Published: (2024)
The Neural Network Approach to Inverse Problems in Differential Equations
by: Xu, Kailai, et al.
Published: (2019)
by: Xu, Kailai, et al.
Published: (2019)
Deep Finite Volume Method for Partial Differential Equations
by: Cen, Jianhuan, et al.
Published: (2023)
by: Cen, Jianhuan, et al.
Published: (2023)
General-Kindred Physics-Informed Neural Network to the Solutions of Singularly Perturbed Differential Equations
by: Wang, Sen, et al.
Published: (2024)
by: Wang, Sen, et al.
Published: (2024)
Quantum Recurrent Neural Networks with Encoder-Decoder for Time-Dependent Partial Differential Equations
by: Chen, Yuan, et al.
Published: (2025)
by: Chen, Yuan, et al.
Published: (2025)
Global-in-time energy stability analysis for the exponential time differencing Runge-Kutta scheme for the phase field crystal equation
by: Li, Xiao, et al.
Published: (2024)
by: Li, Xiao, et al.
Published: (2024)
Similar Items
-
A Structure-Preserving Framework for Solving Parabolic Partial Differential Equations with Neural Networks
by: Chen, Gaohang, et al.
Published: (2025) -
Reduced Basis Methods for Parametric Steady-State Radiative Transfer Equation
by: Matsuda, Kimberly, et al.
Published: (2025) -
Solving Partial Differential Equations Using Artificial Neural Networks
by: Uriarte, Carlos
Published: (2024) -
Encoded Forward Backward Stochastic Neural Network for High-Dimensional Backward Stochastic Differential Equations and Parabolic Partial Differential Equations
by: Zhang, Zhao, et al.
Published: (2026) -
A Multiple Transferable Neural Network Method with Domain Decomposition for Elliptic Interface Problems
by: Lu, Tianzheng, et al.
Published: (2025)