Integral Operator Approaches for Scattered Data Fitting on Spheres
Fuente:
arXiv
Saved in:
| Main Author: | Lin, Shao-Bo |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Universal Approximation of Operators with Transformers and Neural Integral Operators
by: Zappala, Emanuele, et al.
Published: (2024)
by: Zappala, Emanuele, et al.
Published: (2024)
Reduced-Basis Deep Operator Learning for Parametric PDEs with Independently Varying Boundary and Source Data
by: Wang, Yueqi, et al.
Published: (2025)
by: Wang, Yueqi, et al.
Published: (2025)
Neural Operators with Localized Integral and Differential Kernels
by: Liu-Schiaffini, Miguel, et al.
Published: (2024)
by: Liu-Schiaffini, Miguel, et al.
Published: (2024)
Solving Poisson Equations using Neural Walk-on-Spheres
by: Nam, Hong Chul, et al.
Published: (2024)
by: Nam, Hong Chul, et al.
Published: (2024)
Condition Numbers and Eigenvalue Spectra of Shallow Networks on Spheres
by: Liu, Xinliang, et al.
Published: (2025)
by: Liu, Xinliang, et al.
Published: (2025)
Data Complexity Estimates for Operator Learning
by: Kovachki, Nikola B., et al.
Published: (2024)
by: Kovachki, Nikola B., et al.
Published: (2024)
A Hybrid Kernel-Free Boundary Integral Method with Operator Learning for Solving Parametric Partial Differential Equations In Complex Domains
by: Ling, Shuo, et al.
Published: (2024)
by: Ling, Shuo, et al.
Published: (2024)
Sharp Lower Bounds for Linearized ReLU^k Approximation on the Sphere
by: Mao, Tong, et al.
Published: (2025)
by: Mao, Tong, et al.
Published: (2025)
Integral regularization PINNs for evolution equations
by: Feng, Xiaodong, et al.
Published: (2025)
by: Feng, Xiaodong, et al.
Published: (2025)
Multi-scale DeepOnet (Mscale-DeepOnet) for Mitigating Spectral Bias in Learning High Frequency Operators of Oscillatory Functions
by: Wang, Bo, et al.
Published: (2025)
by: Wang, Bo, et al.
Published: (2025)
Stochastic Fractional Neural Operators: A Symmetrized Approach to Modeling Turbulence in Complex Fluid Dynamics
by: Santos, Rômulo Damasclin Chaves dos, et al.
Published: (2025)
by: Santos, Rômulo Damasclin Chaves dos, et al.
Published: (2025)
Stabilizing and Solving Unique Continuation Problems by Parameterizing Data and Learning Finite Element Solution Operators
by: Burman, Erik, et al.
Published: (2024)
by: Burman, Erik, et al.
Published: (2024)
DeltaPhi: Physical States Residual Learning for Neural Operators in Data-Limited PDE Solving
by: Yue, Xihang, et al.
Published: (2024)
by: Yue, Xihang, et al.
Published: (2024)
Data-Efficient Kernel Methods for Learning Differential Equations and Their Solution Operators: Algorithms and Error Analysis
by: Jalalian, Yasamin, et al.
Published: (2025)
by: Jalalian, Yasamin, et al.
Published: (2025)
Deep Neural Network Solutions for Oscillatory Fredholm Integral Equations
by: Jiang, Jie, et al.
Published: (2024)
by: Jiang, Jie, et al.
Published: (2024)
Operator Learning of Lipschitz Operators: An Information-Theoretic Perspective
by: Lanthaler, Samuel
Published: (2024)
by: Lanthaler, Samuel
Published: (2024)
MODNO: Multi Operator Learning With Distributed Neural Operators
by: Zhang, Zecheng
Published: (2024)
by: Zhang, Zecheng
Published: (2024)
Data-Driven, ML-assisted Approaches to Problem Well-Posedness
by: Bertalan, Tom, et al.
Published: (2025)
by: Bertalan, Tom, et al.
Published: (2025)
Conformalized-DeepONet: A Distribution-Free Framework for Uncertainty Quantification in Deep Operator Networks
by: Moya, Christian, et al.
Published: (2024)
by: Moya, Christian, et al.
Published: (2024)
Back-Projection Diffusion: Solving the Wideband Inverse Scattering Problem with Diffusion Models
by: Zhang, Borong, et al.
Published: (2024)
by: Zhang, Borong, et al.
Published: (2024)
Solving the Wide-band Inverse Scattering Problem via Equivariant Neural Networks
by: Zhang, Borong, et al.
Published: (2022)
by: Zhang, Borong, et al.
Published: (2022)
Solving High-Dimensional Partial Integral Differential Equations: The Finite Expression Method
by: Hardwick, Gareth, et al.
Published: (2024)
by: Hardwick, Gareth, et al.
Published: (2024)
UFO: A Domain-Unification-Free Operator Framework for Generalized Operator Learning
by: Qiao, Hanli, et al.
Published: (2026)
by: Qiao, Hanli, et al.
Published: (2026)
Identifying Best Practice Melting Patterns in Induction Furnaces: A Data-Driven Approach Using Time Series KMeans Clustering and Multi-Criteria Decision Making
by: Howard, Daniel Anthony, et al.
Published: (2024)
by: Howard, Daniel Anthony, et al.
Published: (2024)
Kernel Neural Operators (KNOs) for Scalable, Memory-efficient, Geometrically-flexible Operator Learning
by: Lowery, Matthew, et al.
Published: (2024)
by: Lowery, Matthew, et al.
Published: (2024)
Stochastic Dimension Implicit Functional Projections for Exact Integral Conservation in High-Dimensional PINNs
by: Liang, Zhangyong
Published: (2026)
by: Liang, Zhangyong
Published: (2026)
Continuum Attention for Neural Operators
by: Calvello, Edoardo, et al.
Published: (2024)
by: Calvello, Edoardo, et al.
Published: (2024)
Operator Learning: Algorithms and Analysis
by: Kovachki, Nikola B., et al.
Published: (2024)
by: Kovachki, Nikola B., et al.
Published: (2024)
The Parametric Complexity of Operator Learning
by: Lanthaler, Samuel, et al.
Published: (2023)
by: Lanthaler, Samuel, et al.
Published: (2023)
Operator Learning at Machine Precision
by: Bacho, Aras, et al.
Published: (2025)
by: Bacho, Aras, et al.
Published: (2025)
fPINN-DeepONet: A Physics-Informed Operator Learning Framework for Multi-term Time-fractional Mixed Diffusion-wave Equations
by: Lu, Binghang, et al.
Published: (2026)
by: Lu, Binghang, et al.
Published: (2026)
A Boundary Integral-based Neural Operator for Mesh Deformation
by: Wu, Zhengyu, et al.
Published: (2026)
by: Wu, Zhengyu, et al.
Published: (2026)
Data-driven Model Reduction for Soft Robots via Lagrangian Operator Inference
by: Sharma, Harsh, et al.
Published: (2024)
by: Sharma, Harsh, et al.
Published: (2024)
Leray-Schauder Mappings for Operator Learning
by: Zappala, Emanuele
Published: (2024)
by: Zappala, Emanuele
Published: (2024)
SpectraKAN: Conditioning Spectral Operators
by: Cheng, Chun-Wun, et al.
Published: (2026)
by: Cheng, Chun-Wun, et al.
Published: (2026)
Spectral Audit of In-Context Operator Networks
by: Gao, Zhiwei, et al.
Published: (2026)
by: Gao, Zhiwei, et al.
Published: (2026)
Solving PDEs on Spheres with Physics-Informed Convolutional Neural Networks
by: Lei, Guanhang, et al.
Published: (2023)
by: Lei, Guanhang, et al.
Published: (2023)
Physics-Informed Geometry-Aware Neural Operator
by: Zhong, Weiheng, et al.
Published: (2024)
by: Zhong, Weiheng, et al.
Published: (2024)
A Mathematical Analysis of Neural Operator Behaviors
by: Le, Vu-Anh, et al.
Published: (2024)
by: Le, Vu-Anh, et al.
Published: (2024)
Nonlocality and Nonlinearity Implies Universality in Operator Learning
by: Lanthaler, Samuel, et al.
Published: (2023)
by: Lanthaler, Samuel, et al.
Published: (2023)
Similar Items
-
Universal Approximation of Operators with Transformers and Neural Integral Operators
by: Zappala, Emanuele, et al.
Published: (2024) -
Reduced-Basis Deep Operator Learning for Parametric PDEs with Independently Varying Boundary and Source Data
by: Wang, Yueqi, et al.
Published: (2025) -
Neural Operators with Localized Integral and Differential Kernels
by: Liu-Schiaffini, Miguel, et al.
Published: (2024) -
Solving Poisson Equations using Neural Walk-on-Spheres
by: Nam, Hong Chul, et al.
Published: (2024) -
Condition Numbers and Eigenvalue Spectra of Shallow Networks on Spheres
by: Liu, Xinliang, et al.
Published: (2025)