Monotonic Gaussian process for physics-constrained machine learning with materials science applications.
Anh TranKathryn A. MaupinTheron RodgersPublished in: CoRR (2022)
Keyphrases
- gaussian process
- materials science
- machine learning
- model selection
- gaussian processes
- computer science
- approximate inference
- gaussian process regression
- regression model
- related fields
- artificial intelligence
- hyperparameters
- latent variables
- scientific data
- bayesian framework
- semi supervised
- covariance function
- knowledge acquisition
- knowledge representation
- sparse approximations
- learning algorithm
- expectation propagation
- decision trees
- cross validation
- gaussian process models
- natural language
- data mining
- data analysis
- em algorithm
- computational intelligence
- supervised learning
- active learning
- bayesian inference
- researchers and practitioners
- database systems
- edge detection