Approximating Gaussian Process Emulators with Linear Inequality Constraints and Noisy Observations via MC and MCMC.
Andrés F. López-LoperaFrançois BachocNicolas DurrandeOlivier RoustantPublished in: CoRR (2019)
Keyphrases
- gaussian process
- noisy observations
- inequality constraints
- approximate inference
- expectation propagation
- gaussian processes
- constrained optimization
- hyperparameters
- nonlinear programming
- bayesian framework
- equality constraints
- model selection
- regression model
- interior point methods
- markov chain monte carlo
- latent variables
- semi supervised
- closed form
- bayesian inference
- evolutionary algorithm
- graphical models
- cross validation
- linear constraints
- generative model
- prior knowledge
- convex optimization
- parameter estimation
- em algorithm
- super resolution
- support vector