VI-PINNs: Variance-involved Physics-informed Neural Networks for Fast and Accurate Prediction of Partial Differential Equations.
Bin ShanYe LiShengjun HuangPublished in: CoRR (2022)
Keyphrases
- partial differential equations
- neural network
- numerical solution
- anisotropic diffusion
- prediction error
- image denoising
- level set
- image enhancement
- image processing
- multiscale
- fourth order
- pattern recognition
- numerical algorithms
- numerical scheme
- energy functional
- finite difference method
- differential equations
- numerical methods
- mathematical morphology
- finite difference
- artificial neural networks
- high quality
- problems in image processing
- curve evolution
- image segmentation
- nonlinear partial differential equations
- covariance matrix
- high order
- higher order
- diffusion equation
- nonlinear diffusion
- multiresolution
- boundary value problem