A machine learning pipeline for autonomous numerical analytic continuation of Dyson-Schwinger equations.
Andreas WindischThomas GallienChristopher SchwarzlmüllerPublished in: CoRR (2021)
Keyphrases
- machine learning
- human intelligence
- numerical methods
- finite difference
- machine intelligence
- text mining
- machine learning methods
- pattern recognition
- differential equations
- data mining
- knowledge discovery
- learning tasks
- sensitivity analysis
- numerical solution
- explanation based learning
- inductive learning
- computer science
- decision trees
- feature selection
- artificial intelligence
- knowledge acquisition
- machine learning algorithms
- numerical analysis
- support vector machine
- cooperative
- machine learning approaches
- computer vision
- numerical algorithms
- processing pipeline
- linear equations
- stochastic differential equations
- linear systems
- inductive logic programming
- statistical methods
- information processing
- computational intelligence
- supervised learning
- active learning