Meta-learning pseudo-differential operators with deep neural networks
From MaRDI portal
Publication:2123371
DOI10.1016/j.jcp.2020.109309OpenAlexW3004630109MaRDI QIDQ2123371
Yu-Wei Fan, Lexing Ying, Jordi Feliu-Fabà
Publication date: 8 April 2022
Published in: Journal of Computational Physics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1906.06782
Green's functionsradiative transfer equationconvolutional neural networksmeta-learningdeep neural networksnonstandard wavelet form
Related Items (7)
Symplectic neural networks in Taylor series form for Hamiltonian systems ⋮ Deep microlocal reconstruction for limited-angle tomography ⋮ Principled interpolation of Green's functions learned from data ⋮ A Reduced Order Schwarz Method for Nonlinear Multiscale Elliptic Equations Based on Two-Layer Neural Networks ⋮ Learning elliptic partial differential equations with randomized linear algebra ⋮ Solving traveltime tomography with deep learning ⋮ The Random Feature Model for Input-Output Maps between Banach Spaces
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Deep learning-based numerical methods for high-dimensional parabolic partial differential equations and backward stochastic differential equations
- A sparse matrix arithmetic based on \({\mathfrak H}\)-matrices. I: Introduction to \({\mathfrak H}\)-matrices
- DGM: a deep learning algorithm for solving partial differential equations
- Fast algorithms for integral formulations of steady-state radiative transfer equation
- BCR-net: A neural network based on the nonstandard wavelet form
- A fast algorithm for radiative transport in isotropic media
- Solving electrical impedance tomography with deep learning
- Neural network as a function approximator and its application in solving differential equations
- Solving for high-dimensional committor functions using artificial neural networks
- A multiscale neural network based on hierarchical nested bases
- Discrete Symbol Calculus
- Fast wavelet transforms and numerical algorithms I
- Orthonormal bases of compactly supported wavelets
- Solving the quantum many-body problem with artificial neural networks
- An introduction to hierarchical matrices
- Solving high-dimensional partial differential equations using deep learning
- A Multiscale Neural Network Based on Hierarchical Matrices
- SwitchNet: A Neural Network Model for Forward and Inverse Scattering Problems
- An Introduction to Pseudo-Differential Operators
This page was built for publication: Meta-learning pseudo-differential operators with deep neural networks
