Cover Image

Learning Epidemiological Dynamics via the Finite Expression Method

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Du, Jianda, Liang, Senwei, Wang, Chunmei
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Numerical Analysis
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Finite Expression Method for Solving High-Dimensional Partial Differential Equations
by: Liang, Senwei, et al.
Published: (2022)

Solving High-Dimensional Partial Integral Differential Equations: The Finite Expression Method
by: Hardwick, Gareth, et al.
Published: (2024)

Finite Expression Methods for Discovering Physical Laws from Data
by: Jiang, Zhongyi, et al.
Published: (2023)

Solving PDEs on Unknown Manifolds with Machine Learning
by: Liang, Senwei, et al.
Published: (2021)

Multi-Scale Finite Expression Method for PDEs with Oscillatory Solutions on Complex Domains
by: Hardwick, Gareth, et al.
Published: (2025)

AutoNumerics: An Autonomous, PDE-Agnostic Multi-Agent Pipeline for Scientific Computing
by: Du, Jianda, et al.
Published: (2026)

A Fast Algorithm for the Finite Expression Method in Learning Dynamics on Complex Networks
by: Song, Zezheng, et al.
Published: (2024)

Identifying Unknown Stochastic Dynamics via Finite expression methods
by: Liang, Senwei, et al.
Published: (2025)

A Finite Expression Method for Solving High-Dimensional Committor Problems
by: Song, Zezheng, et al.
Published: (2023)

Solving Inverse Parametrized Problems via Finite Elements and Extreme Learning Networks
by: Burman, Erik, et al.
Published: (2026)

Learn Singularly Perturbed Solutions via Homotopy Dynamics
by: Chen, Chuqi, et al.
Published: (2025)

Learned Finite Element-based Regularization of the Inverse Problem in Electrocardiographic Imaging
by: Haas, Manuel, et al.
Published: (2026)

An Overview on Machine Learning Methods for Partial Differential Equations: from Physics Informed Neural Networks to Deep Operator Learning
by: Gonon, Lukas, et al.
Published: (2024)

A Simple Weak Galerkin Finite Element Method for Convection-Diffusion-Reaction Equations on Nonconvex Polytopal Meshes
by: Wang, Chunmei, et al.
Published: (2026)

A Simple Weak Galerkin Finite Element Method for a Class of Fourth-Order Problems in Fluorescence Tomography
by: Wang, Chunmei, et al.
Published: (2025)

Auto-Stabilized Weak Galerkin Finite Element Methods for Biot's consolidation model on Non-Convex Polytopal Meshes
by: Wang, Chunmei, et al.
Published: (2026)

H-FEX: A Symbolic Learning Method for Hamiltonian Systems
by: Lai, Jasen, 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)

KKANs: Kurkova-Kolmogorov-Arnold Networks and Their Learning Dynamics
by: Toscano, Juan Diego, et al.
Published: (2024)

The Poisson Midpoint Method for Langevin Dynamics: Provably Efficient Discretization for Diffusion Models
by: Kandasamy, Saravanan, et al.
Published: (2024)

CONFIDE: Contextual Finite Differences Modelling of PDEs
by: Linial, Ori, et al.
Published: (2023)

Multi-Preconditioned LBFGS for Training Finite-Basis PINNs
by: Salvadó-Benasco, Marc, et al.
Published: (2026)

Learning Singularity-Encoded Green's Functions with Application to Iterative Methods
by: Sun, Qi, et al.
Published: (2025)

Artifacts of Numerical Integration in Learning Dynamical Systems
by: Lu, Bing-Ze, et al.
Published: (2025)

Learning Stochastic Dynamical Systems with Structured Noise
by: Guo, Ziheng, et al.
Published: (2025)

Multilevel CNNs for Parametric PDEs based on Adaptive Finite Elements
by: Schütte, Janina Enrica, et al.
Published: (2024)

Solving and learning advective multiscale Darcian dynamics with the Neural Basis Method
by: Wang, Yuhe, et al.
Published: (2026)

Predictions Based on Pixel Data: Insights from PDEs and Finite Differences
by: Celledoni, Elena, et al.
Published: (2023)

Solving Roughly Forced Nonlinear PDEs via Misspecified Kernel Methods and Neural Networks
by: Baptista, Ricardo, et al.
Published: (2025)

Data-Parallel Neural Network Training via Nonlinearly Preconditioned Trust-Region Method
by: Alegría, Samuel A. Cruz, et al.
Published: (2025)

Machine Learning-Based Nonlinear Nudging for Chaotic Dynamical Systems
by: Oh, Jaemin, et al.
Published: (2025)

When do World Models Successfully Learn Dynamical Systems?
by: Ross, Edmund, et al.
Published: (2025)

Variational Matrix-Learning Fourier Networks for Parametric Multiphysics Surrogates
by: Li, Xinyu, et al.
Published: (2026)

A Data-Driven Interpolation Method on Smooth Manifolds via Diffusion Processes and Voronoi Tessellations
by: Gomez, Alvaro Almeida
Published: (2025)

An Iterative Deep Ritz Method for Monotone Elliptic Problems
by: Hu, Tianhao, et al.
Published: (2025)

Learning Discontinuous Galerkin Solutions to Elliptic Problems via Small Linear Convolutional Neural Networks
by: Celaya, Adrian, et al.
Published: (2025)

Data-Efficient Kernel Methods for Learning Differential Equations and Their Solution Operators: Algorithms and Error Analysis
by: Jalalian, Yasamin, et al.
Published: (2025)

An Enhanced Zeroth-Order Stochastic Frank-Wolfe Framework for Constrained Finite-Sum Optimization
by: Ye, Haishan, et al.
Published: (2025)

Learning Sparse Approximate Inverse Preconditioners for Conjugate Gradient Solvers on GPUs
by: Yang, Zherui, et al.
Published: (2025)

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