Learning High-dimensional Ionic Model Dynamics Using Fourier Neural Operators
Fuente:
arXiv
Enregistré dans:
| Auteurs principaux: | Pellegrini, Luca, Ghiotto, Massimiliano, Centofanti, Edoardo, Pavarino, Luca Franco |
|---|---|
| Format: | Preprint |
| Publié: |
2025
|
| Sujets: | |
| Accès en ligne: | |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
Learning the Hodgkin-Huxley Model with Operator Learning Techniques
par: Centofanti, Edoardo, et autres
Publié: (2024)
par: Centofanti, Edoardo, et autres
Publié: (2024)
HyperNOs: Automated and Parallel Library for Neural Operators Research
par: Ghiotto, Massimiliano
Publié: (2025)
par: Ghiotto, Massimiliano
Publié: (2025)
Learning cardiac activation and repolarization times with operator learning
par: Centofanti, Edoardo, et autres
Publié: (2025)
par: Centofanti, Edoardo, et autres
Publié: (2025)
A Neural Latent Dynamics Approach for Solving Inverse Problems in Cardiac Electrophysiology
par: Centofanti, Edoardo, et autres
Publié: (2026)
par: Centofanti, Edoardo, et autres
Publié: (2026)
Translation Invariance of Neural Operators for the FitzHugh-Nagumo Model
par: Pellegrini, Luca
Publié: (2026)
par: Pellegrini, Luca
Publié: (2026)
Parameter Robust Isogeometric Methods for a Four-Field Formulation of Biot's Consolidation Model
par: Chu, Hanyu, et autres
Publié: (2025)
par: Chu, Hanyu, et autres
Publié: (2025)
Fourier Neural Operator with Learned Deformations for PDEs on General Geometries
par: Li, Zongyi, et autres
Publié: (2022)
par: Li, Zongyi, et autres
Publié: (2022)
Approximating Numerical Fluxes Using Fourier Neural Operators for Hyperbolic Conservation Laws
par: Kim, Taeyoung, et autres
Publié: (2024)
par: Kim, Taeyoung, et autres
Publié: (2024)
Continuum Attention for Neural Operators
par: Calvello, Edoardo, et autres
Publié: (2024)
par: Calvello, Edoardo, et autres
Publié: (2024)
Block BDDC/FETI-DP Preconditioners for Three-Field mixed finite element Discretizations of Biot's consolidation model
par: Chu, Hanyu, et autres
Publié: (2025)
par: Chu, Hanyu, et autres
Publié: (2025)
Component Fourier Neural Operator for Singularly Perturbed Differential Equations
par: Li, Ye, et autres
Publié: (2024)
par: Li, Ye, et autres
Publié: (2024)
Fourier Neural Operators for Non-Markovian Processes:Approximation Theorems and Experiments
par: Lee, Wonjae, et autres
Publié: (2025)
par: Lee, Wonjae, et autres
Publié: (2025)
Beyond Regular Grids: Fourier-Based Neural Operators on Arbitrary Domains
par: Lingsch, Levi, et autres
Publié: (2023)
par: Lingsch, Levi, et autres
Publié: (2023)
Controlling Statistical, Discretization, and Truncation Errors in Learning Fourier Linear Operators
par: Subedi, Unique, et autres
Publié: (2024)
par: Subedi, Unique, et autres
Publié: (2024)
Windowed Fourier Propagator: A Frequency-Local Neural Operator for Wave Equations in Inhomogeneous Media
par: Cai, Yiyang, et autres
Publié: (2026)
par: Cai, Yiyang, et autres
Publié: (2026)
MODNO: Multi Operator Learning With Distributed Neural Operators
par: Zhang, Zecheng
Publié: (2024)
par: Zhang, Zecheng
Publié: (2024)
Operator Learning at Machine Precision
par: Bacho, Aras, et autres
Publié: (2025)
par: Bacho, Aras, et autres
Publié: (2025)
Stochastic Fractional Neural Operators: A Symmetrized Approach to Modeling Turbulence in Complex Fluid Dynamics
par: Santos, Rômulo Damasclin Chaves dos, et autres
Publié: (2025)
par: Santos, Rômulo Damasclin Chaves dos, et autres
Publié: (2025)
Neural Operator: Learning Maps Between Function Spaces
par: Kovachki, Nikola, et autres
Publié: (2021)
par: Kovachki, Nikola, et autres
Publié: (2021)
Kernel Neural Operators (KNOs) for Scalable, Memory-efficient, Geometrically-flexible Operator Learning
par: Lowery, Matthew, et autres
Publié: (2024)
par: Lowery, Matthew, et autres
Publié: (2024)
High-fidelity Multiphysics Modelling for Rapid Predictions Using Physics-informed Parallel Neural Operator
par: Yuan, Biao, et autres
Publié: (2025)
par: Yuan, Biao, et autres
Publié: (2025)
ZNO: Stable Rational Neural Operators in the Z-Domain for Discrete-Time Dynamics
par: Zhu, Xianli, et autres
Publié: (2026)
par: Zhu, Xianli, et autres
Publié: (2026)
Operator Learning for Smoothing and Forecasting
par: Calvello, Edoardo, et autres
Publié: (2026)
par: Calvello, Edoardo, et autres
Publié: (2026)
Physics-embedded Fourier Neural Network for Partial Differential Equations
par: Xu, Qingsong, et autres
Publié: (2024)
par: Xu, Qingsong, et autres
Publié: (2024)
Equivariant Graph Neural Operator for Modeling 3D Dynamics
par: Xu, Minkai, et autres
Publié: (2024)
par: Xu, Minkai, et autres
Publié: (2024)
Universal Approximation of Operators with Transformers and Neural Integral Operators
par: Zappala, Emanuele, et autres
Publié: (2024)
par: Zappala, Emanuele, et autres
Publié: (2024)
Enhancing Solutions for Complex PDEs: Introducing Complementary Convolution and Equivariant Attention in Fourier Neural Operators
par: Zhao, Xuanle, et autres
Publié: (2023)
par: Zhao, Xuanle, et autres
Publié: (2023)
Learn to Evolve: Self-supervised Neural JKO Operator for Wasserstein Gradient Flow
par: Feng, Xue, et autres
Publié: (2026)
par: Feng, Xue, et autres
Publié: (2026)
Monotone Peridynamic Neural Operator for Nonlinear Material Modeling with Conditionally Unique Solutions
par: Wang, Jihong, et autres
Publié: (2025)
par: Wang, Jihong, et autres
Publié: (2025)
Fast Kernel Summation in High Dimensions via Slicing and Fourier Transforms
par: Hertrich, Johannes
Publié: (2024)
par: Hertrich, Johannes
Publié: (2024)
Neural Interpretable PDEs: Harmonizing Fourier Insights with Attention for Scalable and Interpretable Physics Discovery
par: Liu, Ning, et autres
Publié: (2025)
par: Liu, Ning, et autres
Publié: (2025)
Physics-Informed Geometry-Aware Neural Operator
par: Zhong, Weiheng, et autres
Publié: (2024)
par: Zhong, Weiheng, et autres
Publié: (2024)
A Mathematical Analysis of Neural Operator Behaviors
par: Le, Vu-Anh, et autres
Publié: (2024)
par: Le, Vu-Anh, et autres
Publié: (2024)
CFO: Learning Continuous-Time PDE Dynamics via Flow-Matched Neural Operators
par: Hou, Xianglong, et autres
Publié: (2025)
par: Hou, Xianglong, et autres
Publié: (2025)
Mamba Neural Operator: Who Wins? Transformers vs. State-Space Models for PDEs
par: Cheng, Chun-Wun, et autres
Publié: (2024)
par: Cheng, Chun-Wun, et autres
Publié: (2024)
DeltaPhi: Physical States Residual Learning for Neural Operators in Data-Limited PDE Solving
par: Yue, Xihang, et autres
Publié: (2024)
par: Yue, Xihang, et autres
Publié: (2024)
An Overview on Machine Learning Methods for Partial Differential Equations: from Physics Informed Neural Networks to Deep Operator Learning
par: Gonon, Lukas, et autres
Publié: (2024)
par: Gonon, Lukas, et autres
Publié: (2024)
Variational Matrix-Learning Fourier Networks for Parametric Multiphysics Surrogates
par: Li, Xinyu, et autres
Publié: (2026)
par: Li, Xinyu, et autres
Publié: (2026)
Operator Learning of Lipschitz Operators: An Information-Theoretic Perspective
par: Lanthaler, Samuel
Publié: (2024)
par: Lanthaler, Samuel
Publié: (2024)
Multi-Level Monte Carlo Training of Neural Operators
par: Rowbottom, James, et autres
Publié: (2025)
par: Rowbottom, James, et autres
Publié: (2025)
Documents similaires
-
Learning the Hodgkin-Huxley Model with Operator Learning Techniques
par: Centofanti, Edoardo, et autres
Publié: (2024) -
HyperNOs: Automated and Parallel Library for Neural Operators Research
par: Ghiotto, Massimiliano
Publié: (2025) -
Learning cardiac activation and repolarization times with operator learning
par: Centofanti, Edoardo, et autres
Publié: (2025) -
A Neural Latent Dynamics Approach for Solving Inverse Problems in Cardiac Electrophysiology
par: Centofanti, Edoardo, et autres
Publié: (2026) -
Translation Invariance of Neural Operators for the FitzHugh-Nagumo Model
par: Pellegrini, Luca
Publié: (2026)