Machine Learning Inter-Atomic Potentials Generation Driven by Active Learning: A Case Study for Amorphous and Liquid Hafnium dioxide.
Ganesh SivaramanAnand Narayanan KrishnamoorthyMatthias BaurChristian HolmMarius StanGábor CsányiChris J. BenmoreÁlvaro Vázquez-MayagoitiaPublished in: CoRR (2019)
Keyphrases
- active learning
- machine learning
- learning algorithm
- learning strategies
- semi supervised learning
- machine learning methods
- pattern recognition
- transfer learning
- supervised machine learning
- thin film
- experimental design
- semi supervised
- data driven
- labeled data
- selective sampling
- machine learning algorithms
- higher order
- learning tasks
- test bed
- training examples
- unlabeled data
- computational intelligence
- supervised learning
- learning process
- training set
- case study
- inductive learning
- random sampling
- inductive logic programming
- pool based active learning
- learning systems
- support vector machine
- computer vision
- artificial intelligence
- data mining
- kernel methods
- statistical methods
- high order
- data analysis
- machine learning approaches
- feature selection
- generation process
- sample selection
- data sets