Machine Learning to Approximate Solutions of Ordinary Differential Equations: Neural Networks vs. Linear Regressors.
Georg EngelPublished in: ICCS (4) (2019)
Keyphrases
- approximate solutions
- ordinary differential equations
- machine learning
- neural network
- numerical integration
- pattern recognition
- differential equations
- np hard
- dynamic systems
- numerical solution
- optimal solution
- exact solution
- taylor series
- mathematical models
- machine learning methods
- energy function
- artificial intelligence
- computer vision
- learning algorithm
- low order
- partial differential equations
- transfer learning
- finite element
- graphical models
- biological systems
- knowledge discovery
- linear systems
- genetic algorithm
- data sets