Deep ReLU neural network approximation of parametric and stochastic elliptic PDEs with lognormal inputs.
Dinh DungVan Kien NguyenDuong Thanh PhamPublished in: CoRR (2021)
Keyphrases
- neural network
- partial differential equations
- solving partial differential equations
- approximation schemes
- numerical methods
- discrete random variables
- hopfield neural network
- artificial neural networks
- anisotropic diffusion
- numerical scheme
- back propagation
- monte carlo sampling
- level set
- image enhancement
- image denoising
- numerical solution
- difference equations
- stage stochastic programs
- neural network model
- boundary value problem
- error bounds
- closed form
- mumford shah model
- approximation methods
- fuzzy logic
- feed forward
- image processing
- multiscale
- feed forward neural networks
- queueing networks
- power law
- recurrent neural networks
- multilayer perceptron
- neural network is trained
- approximation algorithms
- approximation error
- hidden layer
- monte carlo
- self organizing maps
- fault diagnosis
- pattern recognition
- genetic algorithm