Approximate Gaussian process inference for the drift function in stochastic differential equations.
Andreas RuttorPhilipp BatzManfred OpperPublished in: NIPS (2013)
Keyphrases
- gaussian process
- covariance function
- expectation propagation
- gaussian processes
- poisson process
- gaussian process regression
- brownian motion
- approximate inference
- regression model
- stochastic differential equations
- reproducing kernel hilbert space
- hyperparameters
- model selection
- bayesian inference
- bayesian framework
- latent variables
- semi supervised
- density estimation
- incomplete data
- random fields
- prior information
- non stationary
- bayesian networks