:: Library Catalog

Copertina

Salvato in:

Dettagli Bibliografici
Autori principali:	Zhu, Xianli, Yin, Jia
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Machine Learning Numerical Analysis
Accesso online:	https://arxiv.org/abs/2605.02356
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

WINO: A Weak-Form Physics Informed Neural Operator for Hyperelasticity on Variable Domains
di: Zhu, Bokai, et al.
Pubblicazione: (2026)

Beyond Regular Grids: Fourier-Based Neural Operators on Arbitrary Domains
di: Lingsch, Levi, et al.
Pubblicazione: (2023)

ReBaNO: Reduced Basis Neural Operator Mitigating Generalization Gaps and Achieving Discretization Invariance
di: Zheng, Haolan, et al.
Pubblicazione: (2025)

Latent Neural Operator Pretraining for Solving Time-Dependent PDEs
di: Wang, Tian, et al.
Pubblicazione: (2024)

A Discrete Neural Operator with Adaptive Sampling for Surrogate Modeling of Parametric Transient Darcy Flows in Porous Media
di: Chen, Zhenglong, et al.
Pubblicazione: (2025)

A Hybridizable Neural Time Integrator for Stable Autoregressive Forecasting
di: Kinch, Brooks, et al.
Pubblicazione: (2026)

Physics-informed Discretization-independent Deep Compositional Operator Network
di: Zhong, Weiheng, et al.
Pubblicazione: (2024)

Learning High-dimensional Ionic Model Dynamics Using Fourier Neural Operators
di: Pellegrini, Luca, et al.
Pubblicazione: (2025)

CFO: Learning Continuous-Time PDE Dynamics via Flow-Matched Neural Operators
di: Hou, Xianglong, et al.
Pubblicazione: (2025)

UFO: A Domain-Unification-Free Operator Framework for Generalized Operator Learning
di: Qiao, Hanli, et al.
Pubblicazione: (2026)

Controlling Statistical, Discretization, and Truncation Errors in Learning Fourier Linear Operators
di: Subedi, Unique, et al.
Pubblicazione: (2024)

Learning Mesh-Free Discrete Differential Operators with Self-Supervised Graph Neural Networks
di: Starepravo, Lucas Gerken, et al.
Pubblicazione: (2026)

Universal Approximation of Operators with Transformers and Neural Integral Operators
di: Zappala, Emanuele, et al.
Pubblicazione: (2024)

MODNO: Multi Operator Learning With Distributed Neural Operators
di: Zhang, Zecheng
Pubblicazione: (2024)

Continuum Attention for Neural Operators
di: Calvello, Edoardo, et al.
Pubblicazione: (2024)

A Multiple Transferable Neural Network Method with Domain Decomposition for Elliptic Interface Problems
di: Lu, Tianzheng, et al.
Pubblicazione: (2025)

DeltaPhi: Physical States Residual Learning for Neural Operators in Data-Limited PDE Solving
di: Yue, Xihang, et al.
Pubblicazione: (2024)

Stochastic Fractional Neural Operators: A Symmetrized Approach to Modeling Turbulence in Complex Fluid Dynamics
di: Santos, Rômulo Damasclin Chaves dos, et al.
Pubblicazione: (2025)

Autoregression-Free Neural Operators for Time-Dependent PDEs
di: Zhang, Jiaquan, et al.
Pubblicazione: (2026)

Physics-Informed Geometry-Aware Neural Operator
di: Zhong, Weiheng, et al.
Pubblicazione: (2024)

A Mathematical Analysis of Neural Operator Behaviors
di: Le, Vu-Anh, et al.
Pubblicazione: (2024)

Kernel Neural Operators (KNOs) for Scalable, Memory-efficient, Geometrically-flexible Operator Learning
di: Lowery, Matthew, et al.
Pubblicazione: (2024)

Equivariant Graph Neural Operator for Modeling 3D Dynamics
di: Xu, Minkai, et al.
Pubblicazione: (2024)

Discrete Solution Operator Learning for Geometry-Dependent PDEs
di: Bai, Jinshuai, et al.
Pubblicazione: (2026)

$ε$-rank and the Staircase Phenomenon: New Insights into Neural Network Training Dynamics
di: Yang, Jiang, et al.
Pubblicazione: (2024)

Multi-Level Monte Carlo Training of Neural Operators
di: Rowbottom, James, et al.
Pubblicazione: (2025)

Quantitative Approximation for Neural Operators in Nonlinear Parabolic Equations
di: Furuya, Takashi, et al.
Pubblicazione: (2024)

Revisiting Orbital Minimization Method for Neural Operator Decomposition
di: Ryu, J. Jon, et al.
Pubblicazione: (2025)

Neural Operator: Learning Maps Between Function Spaces
di: Kovachki, Nikola, et al.
Pubblicazione: (2021)

Guaranteed Approximation Bounds for Mixed-Precision Neural Operators
di: Tu, Renbo, et al.
Pubblicazione: (2023)

Stability and Discretization Error of State Space Model Neural Operators
di: Bendahi, Abderrahim, et al.
Pubblicazione: (2026)

U-HNO: A U-shaped Hybrid Neural Operator with Sparse-Point Adaptive Routing for Non-stationary PDE Dynamics
di: Ma, Yingzhe, et al.
Pubblicazione: (2026)

Translation Invariance of Neural Operators for the FitzHugh-Nagumo Model
di: Pellegrini, Luca
Pubblicazione: (2026)

Fourier Neural Operator with Learned Deformations for PDEs on General Geometries
di: Li, Zongyi, et al.
Pubblicazione: (2022)

HAMLET: Graph Transformer Neural Operator for Partial Differential Equations
di: Bryutkin, Andrey, et al.
Pubblicazione: (2024)

Blending Neural Operators and Relaxation Methods in PDE Numerical Solvers
di: Zhang, Enrui, et al.
Pubblicazione: (2022)

Long-time Integration of Nonlinear Wave Equations with Neural Operators
di: Lei, Guanhang, et al.
Pubblicazione: (2024)

HyperNOs: Automated and Parallel Library for Neural Operators Research
di: Ghiotto, Massimiliano
Pubblicazione: (2025)

Latent Neural Operator for Solving Forward and Inverse PDE Problems
di: Wang, Tian, et al.
Pubblicazione: (2024)

Component Fourier Neural Operator for Singularly Perturbed Differential Equations
di: Li, Ye, et al.
Pubblicazione: (2024)