A Survey of Interpretability of Machine Learning in Accelerator-based High Energy Physics.
Danielle TurvillLee BarnbyBo YuanAli ZahirPublished in: BDCAT (2020)
Keyphrases
- high energy physics
- machine learning
- scientific data
- pattern recognition
- prediction accuracy
- machine learning methods
- machine learning algorithms
- active learning
- bitmap indices
- computer vision
- parallel implementation
- learning algorithm
- artificial intelligence
- machine learning approaches
- computational biology
- inductive learning
- learning systems
- semi supervised learning
- knowledge acquisition
- knowledge representation
- reinforcement learning
- information retrieval
- data mining
- computational intelligence
- learning tasks
- rule base
- text mining
- natural language processing
- support vector machine
- expert systems
- explanation based learning
- supervised machine learning
- compute intensive