Deep ReLU neural networks overcome the curse of dimensionality when approximating semilinear partial integro-differential equations.
Ariel NeufeldTuan Anh NguyenSizhou WuPublished in: CoRR (2023)
Keyphrases
- differential equations
- neural network
- difference equations
- dynamical systems
- ordinary differential equations
- pattern recognition
- numerical solution
- numerical methods
- artificial neural networks
- boundary value problem
- feed forward artificial neural networks
- back propagation
- partial differential equations
- brownian motion
- fuzzy logic
- image analysis
- nonlinear differential equations
- numerical integration
- runge kutta
- training process
- transmission line
- activation function
- high order
- multiresolution
- feature extraction