A-PINN: Auxiliary physics informed neural networks for forward and inverse problems of nonlinear integro-differential equations.
Lei YuanYi-Qing NiXiang-Yun DengShuo HaoPublished in: J. Comput. Phys. (2022)
Keyphrases
- differential equations
- inverse problems
- neural network
- partial differential equations
- ordinary differential equations
- nonlinear differential equations
- boundary value problem
- difference equations
- image reconstruction
- feed forward artificial neural networks
- global optimization
- convex optimization
- dynamical systems
- artificial neural networks
- numerical solution
- optimization methods
- optimization problems
- pattern recognition
- level set
- image processing
- high order
- image denoising
- early vision
- smoothness constraint
- genetic algorithm
- evolutionary algorithm
- optical flow
- computationally expensive
- high dimensional
- pairwise
- object recognition
- image enhancement
- objective function
- multiscale
- computer vision